22MBA14 Statistics for Managers syllabus for MBA

Introduction to Statistics:

Meaning and Definition, Importance, Types, Measures of Central Tendency -Arithmetic mean, Geometric mean, Harmonic mean, Median, Quartiles, Deciles, Percentiles, Mode. Measures of Dispersion -Range, Quartile deviation, Mean deviation, Standard deviation, Variance, Coefficient of Variation. (Theory and Problem).

Correlation and Regression:

Correlation - Significance, Types, and Methods, Scatter diagram, Karl Pearson correlation, Spearman’s Rank correlation, Regression, Significance, Linear Regression Analysis, Types of regression models, Lines of Regression. (Theory and Problem).

Probability Distribution:

Concept of probability, Counting rules for determining number of outcomes - Permutation and Combination, Rules of probability- Addition and Multiplication, Baye’s Theorem. Concept of Probability Distribution, Theoretical Probability Distributions - Binomial, Poisson, Normal (Problems only on Binomial, Poisson and Normal). (Theory and Problem).

Time Series Analysis:

Objectives, Variations in Time Series. Measurement of Trend, Graphic Method, Moving Average Method, Semi-Average Method, Least Square Method. Measurement of Seasonal Variations- Method of Simple Averages, Ratio to Trend Method-Ratio to Moving Average Method, Link Relative Method. (Theory and Problem).

Hypotheses Testing:

Definition, Types, Procedure for testing, Errors in hypotheses testing. Parametric and Non-Parametric Tests -t-test, z-test, f-test, Chi-square test, u-test, K-W Test (problems on all tests).Analysis of Variance (theory only).

Computer lab for Statistics:

SPSS: Overview of SPSS, Creating, saving and editing files, Importing files from other formats. Transforming Variables - Compute, Multiple responses. Organization and Presentation of Information - Measures of Central Tendency and Variability, Frequency Distributions. Charts and Graphs, Hypotheses testing using means and cross-tabulation, Paired t, Independent sample t, Chi- square. Correlation, Regression Analysis, Linear, Logistic, Analysis of Variance- One Way ANOVA, ANOVA in regression.

Assessment Details (both CIE and SEE)

• The weightage of Continuous Internal Evaluation (CIE) is 50% and for Semester End Exam (SEE) is 50%.
• The minimum passing marks for the CIE is 50% of the maximum marks. Minimum passing marks in SEE is 40% of the maximum marks of SEE.
• A student shall be deemed to have satisfied the academic requirements (passed) and earned the credits allotted to each course if the student secures not less than 50% in the sum total of the CIE (Continuous Internal Evaluation) and SEE (Semester End Examination) taken together.

Continuous Internal Evaluation:

There shall be a maximum of 50 CIE Marks.

• A candidate shall obtain not less than 50% of the maximum marks prescribed for the CIE.
• CIE Marks shall be based on:

a) Tests (for 25Marks) and

b) Assignments, presentations, Quiz, Simulation, Experimentation, Mini project, oral examination, field work and class participation etc., (for 25 Marks) conducted in the respective course. Course instructors are given autonomy in choosing a few of the above based on the subject relevance and should maintain necessary supporting documents for same.

Semester End Examination:

The SEE question paper will be set for 100 marks and the marks scored will be proportionately reduced to 50.

• The question paper will have 8 full questions carrying equal marks.
• Each full question is for 20 marks with 3 sub questions.
• Each full question will have sub question covering all the topics.
• The students will have to answer five full questions; selecting four full question from question number one to seven in the pattern of 3, 7 & 10 Marks and question number eight is compulsory.
• 40 percent theory and 60 percent problems.

Suggested Learning Resources: Books

1. S C Gupta (2018), Fundamentals of Statistics, 7th edition Himalaya Publications.

2. J K Sharma (2020), Business Statistics 5th edition Vikas Publishing House.

3. S P Gupta (2021), Statistical Methods 46th edition Sultan Chand Publications.

4. C R Kothari (2015), Research Methodology- Methods and Techniques, Viswa Prakasam Publications.

5. William E. Wagner, III (2015), Using IBM SPSS- Statistics for Research Methods and Social Science Statistics 5th edition Sage Publications.

Skill Development Activities Suggested

• Role Play Techniques
• Quizzes
• Field Surveys
• Assignments

Course outcome (Course Skill Set)

At the end of the course the student will be able to:

CO1 Understand how to organize, manage, and present the data L2

CO2 Use and apply a wide variety of specific statistical tools L3

CO3 Understand the applications of probability in business L4

CO4 Effectively interpret the results of statistical analysis L5

CO5 Develop competence of using computer packages to solve the problems L6