Practical Exam Problem Set 1: QuestionPaper01.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #1 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 2: QuestionPaper02.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #2 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 3: QuestionPaper03.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #3 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 4: QuestionPaper04.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #4 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 5: QuestionPaper05.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #5 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 6: QuestionPaper06.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #6 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 7: QuestionPaper07.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #7 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 8: QuestionPaper08.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #8 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 9: QuestionPaper09.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #9 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 10: QuestionPaper10.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #10 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 11: QuestionPaper11.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #11 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 12: QuestionPaper12.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #12 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 13: QuestionPaper13.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #13 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 14: QuestionPaper14.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #14 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 15: QuestionPaper15.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #15 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 16: QuestionPaper16.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #16 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 17: QuestionPaper17.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #17 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Statistical Measures & Probability Theory • Central Tendency & Dispersion: Mean \bar{X} = \frac{\sum fX}{N}, Median, Mode, Standard Deviation \sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}, Coefficient of Variation CV = \frac{\sigma}{\bar{X}} \times 100\%. • Probability Distributions: - Binomial Distribution: P(X = r) = \binom{n}{r} p^r q^{n-r}. - Normal Distribution: Standard normal variable Z = \frac{X - \mu}{\sigma}. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Practical Exam Problem Set 18: QuestionPaper18.jpg

Tribhuvan University — BITM / BIM Laboratory Practical Examination Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #18 (of 18) Evaluation Standard: 40 Full Marks Practical Examination 1. Laboratory Problem Statement & Objective This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells). 2. Step-by-Step Computational Procedure & Analytical Solution Inferential Statistics: Correlation & Hypothesis Testing • Karl Pearson's Correlation (r): Measures direction and strength of linear relationship (-1 \le r \le +1). • Linear Regression Equations: Line of Y on X: Y - \bar{Y} = b{yx}(X - \bar{X}) where b{yx} = r \frac{\sigmay}{\sigmax}. • Hypothesis Testing: Formulating H0 and H1, significance level \alpha, calculating test statistic (t-test, z-test), comparing with critical table value to accept or reject H_0. 3. Data Visualization & Verification Output • Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions. • Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms. • Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making. 4. Grading Criteria & Practical Viva Questions • Algorithm & Formula Accuracy: 15 Marks • Tabular Formulation & Execution Results: 15 Marks • Interpretation & Viva-Voce Defense: 10 Marks

Business Statistics Practical Board Examination Scans with Solutions – STT 201

Tribhuvan University

Faculty of Management

Office of the Dean

2021 AD / Regular Examination

Course: STT 201 · Business Statistics

Level: Bachelor of Information Management (BIM) · Semester 3

Full Marks: 40

Time: 2 hrs.

Practical laboratory exam questions and computer statistical problem sets.

Statistical Lab Problem Scans

Solve practical problems using SPSS / MS Excel / manual calculation.

[40 marks]

[10]
Practical Exam Problem Set 1: Question_Paper_01.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #1 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 2: Question_Paper_02.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #2 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 3: Question_Paper_03.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #3 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #4 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 5: Question_Paper_05.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #5 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #6 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 7: Question_Paper_07.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #7 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #8 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 9: Question_Paper_09.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #9 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 10: Question_Paper_10.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #10 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 11: Question_Paper_11.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #11 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 12: Question_Paper_12.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #12 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 13: Question_Paper_13.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #13 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 14: Question_Paper_14.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #14 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 15: Question_Paper_15.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #15 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 16: Question_Paper_16.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #16 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 17: Question_Paper_17.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #17 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory
- Central Tendency & Dispersion: Mean $\bar{X} = \frac{\sum fX}{N}$ , Median, Mode, Standard Deviation $\sigma = \sqrt{\frac{\sum f(X - \bar{X})^2}{N}}$ , Coefficient of Variation $CV = \frac{\sigma}{\bar{X}} \times 100\%$ .
- Probability Distributions:
  
  Binomial Distribution: $P(X = r) = \binom{n}{r} p^r q^{n-r}$ .
  
  Normal Distribution: Standard normal variable $Z = \frac{X - \mu}{\sigma}$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks
[10]
Practical Exam Problem Set 18: Question_Paper_18.jpg
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Tribhuvan University — BITM / BIM Laboratory Practical Examination

Course: STT 201 — Business Statistics Problem Set: Practical Laboratory Problem Set #18 (of 18) Evaluation Standard: 40 Full Marks Practical Examination

1. Laboratory Problem Statement & Objective

This practical examination board problem set tests hands-on computational modeling, practical data manipulation, and software execution in Business Statistics using contemporary analytical tools (MS Excel / SPSS / R / Database Command Shells).

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing
- Karl Pearson’s Correlation ( $r$ ): Measures direction and strength of linear relationship ( $-1 \le r \le +1$ ).
- Linear Regression Equations: Line of $Y$ on $X$ : $Y - \bar{Y} = b_{yx}(X - \bar{X})$ where $b_{yx} = r \frac{\sigma_y}{\sigma_x}$ .
- Hypothesis Testing: Formulating $H_0$ and $H_1$ , significance level $\alpha$ , calculating test statistic ( $t$ -test, $z$ -test), comparing with critical table value to accept or reject $H_0$ .
3. Data Visualization & Verification Output
- Input Data Verification: Verify dataset normality, check for missing values, and validate variable definitions.
- Execution Workflow: Execute designated data transformations, formula evaluations, and computational algorithms.
- Practical Interpretation: All calculated statistical and computational metrics must be accompanied by rigorous academic interpretation linking numerical results to managerial decision-making.
4. Grading Criteria & Practical Viva Questions
- Algorithm & Formula Accuracy: 15 Marks
- Tabular Formulation & Execution Results: 15 Marks
- Interpretation & Viva-Voce Defense: 10 Marks

Past exam papers

Business Statistics Practical Board Examination Scans

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Inferential Statistics: Correlation & Hypothesis Testing

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions

Tribhuvan University — BITM / BIM Laboratory Practical Examination

1. Laboratory Problem Statement & Objective

2. Step-by-Step Computational Procedure & Analytical Solution

Statistical Measures & Probability Theory

3. Data Visualization & Verification Output

4. Grading Criteria & Practical Viva Questions