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Statistics for Management MBA - 1 Semester Anna University
Author Name - Mr. Dileep Singh
ISBN NO - 9789361805431
Syllabus
MB25C01: STATISTICS FOR MANAGEMENT
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 Goodnessof 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)
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Author Name - Mr. Dileep Singh
ISBN NO - 9789361805431
Syllabus
MB25C01: STATISTICS FOR MANAGEMENT
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 Goodnessof 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)
Statistics for Management is a comprehensive course designed to equip MBA students with essential statistical tools and techniques for effective decision-making in business and management. It covers both descriptive and inferential statistics, enabling learners to analyze data, interpret results, and apply quantitative methods to real-world business problems. Topics include measures of central tendency and dispersion, probability distributions, correlation and regression analysis, hypothesis testing, analysis of variance (ANOVA), time series analysis, and decision theory.
This subject emphasizes practical applications of statistics in areas such as marketing research, financial analysis, operations, and strategic planning. With a strong focus on problem-solving and managerial decision-making, the course builds analytical thinking and data-driven decision-making skills, preparing students to handle complex business challenges with confidence.
Anna/MBA/01/01
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