This course will enable the students to assess the knowledge of all the statistical aspects for business decisions in the quantitative manner and preparing the research report using appropriate statistical techniques.
Course |
Learning outcome (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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Course Code |
Course Title |
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24CBTM401 |
Statistics for Business Decisions (Theory)
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CO139: Examine the concept of correlation and regression analysis. CO140: Assess the theory of probability and probability distribution. CO141: Appraise the sampling theory and interpret the results of Z test. CO142: Analyze the results of t test, ANOVA and Chi-square test. CO143: Construct a research report. CO144: Contribute effectively in course-specific interaction |
Approach in teaching: Interactive sessions, Discussion, Tutorials, Reading assignments
Learning activities for the students: Self learning assignments, Solving questions-based problems, Group tasks |
Continuous Assessment Test, Semester end examinations, Quiz, Solving problems in tutorials, Assignments, Presentation, Individual and group projects |
Correlation and Regression Analysis
Correlation Analysis: Meaning and significance. Correlation and Causation, Types of correlation. Methods of studying simple correlation - Scatter diagram, Karl Pearson’s coefficient of correlation, Spearman’s Rank correlation coefficient, Concurrent correlation. Regression Analysis: Meaning and significance, Regression vs. Correlation. Linear Regression, Regression lines (X on Y, Y on X)
Probability Theory and Probability Distribution
Probability: Meaning and need. Theorems of addition and multiplication. Conditional probability. Baye’s Theorem. Probability Distribution: Meaning, characteristics (Expectation and variance) of Binomial, Poisson, and Normal distribution.
Sampling Theory, Test of Significance of large sample
Sampling Theory: Parameter and Statistic, Sampling Distribution of a Statistic and Standard Error of a Statistic Test of Hypothesis: Element and Procedure of Testing a Statistical Hypothesis, Types of Errors. Level of Significance Test of Significance (Large Sample)- Sample Mean, Difference between two Sample Means, Difference between two Standard Deviations, Sample Proportion and Difference between two Sample Proportions.
Test of Significance (Small Sample), Chi-square test and Analysis of Variance Test of Significance (Small Sample): Application of Student’s t- test for Mean, Difference between two Means (Independent and Paired t-test for Difference of Means).
Chi-square test: Definition and Nature, Uses of Chi-Square Test- Test of Goodness of Fit, Test of Independence of Attributes and Test for the Population Variance.
Analysis of Variance: One-way and two-way classification.
Research report writing
Research report writing: Format of research report, presentation, footnote- endnote, bibliography, references.
Suggested Readings:
E-resources: