Statistics for Management - MB25C01

MB25C01 :

Statistics for Management

Course Objectives:

This course aims to provide statistical tools for data-driven decision-making, emphasizing the application of probability, hypothesis testing, regression analysis, parametric and non-parametric methods to enhance analytical skills in business scenarios.

Probability and Probability Distributions: Basic definitions and rules for probability, conditional probability independence of events, Baye‘s theorem, (Theory and Problem) and random variables, Probability distributions: Binomial, Poisson, Uniform and Normal distributions (Problem).

Sampling and Estimation Techniques: Introduction to sampling distributions, sampling distribution of mean and proportion, application of central limit theorem (Theory and Problem), sampling techniques (Problem). Estimation: Point and Interval estimates for population parameters of large sample and small samples, determining the sample size (Problem).

Hypothesis Testing – Parametric Methods (Problem): Hypothesis testing: one sample and two sample tests for means and proportions of large samples (z- test), one sample and two sample tests for means of small samples (t-test), F-test for two sample standard deviations. ANOVA one and two way

Hypothesis Testing – Non-Parametric Methods (Problem): Chi-square test for single sample standard deviation. Chi-square tests for independence of attributes and goodness of fit. Sign test for paired data. Rank sum test. Kolmogorov-Smirnov, test for goodness of fit, comparing two populations. Mann, Whitney U test and Kruskal Wallis test. One sample run test.

Correlation and Regression Analysis (Problem): Correlation, Coefficient of Determination, Rank Correlation, Regression, Estimation of Regressionline, Method of Least Squares, Standard Error of estimate.

Business Analytics Applications & Software Tools: Application of statistics - data visualization and decision making - Case studies using Excel/SPSS/R, Interpretation of output - Business scenarios - applying regression, correlation, and hypothesis tests - Introduction to data-driven storytelling -dashboarding techniques (Theory and Problem)

Weightage: Continuous Assessment: 40%, End Semester Examinations: 60%.

Assessment Methodology: Written Test I & II (60%) Assignment, Presentation, Case Study, Quiz, Simulation, Online Certification, Seminar, Mini project (40%)

References:

1. Levin, R. I., Rubin, D. S., Siddiqui, M. H., & Rastogi, S. (2023). Statistics for management (8th ed.). Pearson Education.

2. Mann, P. S. (2020). Introductory statistics (10th ed.). Wiley Publications.

3. Srivastava, T. N., & Rego, S. (2017). Statistics for management (3rd ed.). Tata McGraw Hill.

4. Black, K. (2023). Applied business statistics (11th ed.). Wiley India.

5. Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2024).

Statistics for business and economics (15th ed.). Thomson/South Western Asia.

6. Gupta, S. C., & Kapoor, V. K. (2024). Fundamentals of applied statistics. Sultan Chand & Sons.