Statistics (FPM)Course Outline

Credits: 3.0 (30 hours)

Objective

This introductory course on statistical methods is aimed at providing doctoral (FPM) students a strong basis in carrying out fundamental statistical analysis with proper understanding of principles behind. Since many of the students are likely/expected to apply some of these techniques in their dissertation, possibly with appropriate adaptation and fine-tuning, adequate emphasis will be given in explaining the assumptions and logic behind the development of these methods. The course does not assume any prior exposure of probability and statistics and hence a brief but focused coverage of probability theory and probability distributions are provided in the first part of the course. Statistical inference, estimation through point and confidence intervals as well as testing of hypothesis concerning mean, proportion and variance for single, two and eventually multiple populations are the key topics of coverage in this course. In addition, selected non-parametric methods along with goodness of fit tests will also be covered. The pedagogy is designed to strike a balance between theoretical treatise, application orientation and software implementation through EXCEL/SPSS with somewhat more emphasis on the first two dimensions.

Textbook:

Business Statistics for Contemporary Decision Making by Ken Black, Wiley Student Edition (Fifth Edition).

Evaluation Procedure

Quizzes and assignments 40%Midterm Examination 20%End term Examination 40%

-------Total 100%

Topics No. of Sessions (1.5 hrs)

Descriptive Statistics 1Data Summarization methods, Measures of Central Tendency, Measures of Dispersion, Graphical presentation, Calculating Mean, mode, median and Variance and Standard deviation from Summarized data

Probability and Probability Distributions 4Basic Concepts of Probability; Bayes’ theorem, Relevance of information, Statistical Independence, Revision of Probabilities Case: How Reliable is Reliable?Discrete Distributions: Hyper Geometric Distribution, Binomial Distribution and Poisson distributionCases: Cleartone radios; Agony of Attrition and Breakdowns on Vacation Continuous distributions: Uniform Distribution; Normal Distribution and Exponential DistributionCases: How much to pack?

Sampling and Sampling Distributions 2Sampling Techniques- Probabilistic Sampling, Convenience Sampling, Judgmental samplingSampling distributions: Sampling distributions of Mean, Proportion, Variance

Point Estimation 1Properties of an estimator

Confidence Interval Estimation 2Interval estimation: Sample mean, Sample proportion and VarianceCase: Is Medworld Cheating?

Hypothesis Testing 4Principles of Statistical Inference; One sample tests; One tailed tests; Two sample testsCase: Chubby Chunky

ANOVA 2Analysis of Variance: One-way analysis of Variance; Two-way Analysis of VarianceCase: Troublesum Trucks

Goodness of Fit Tests and NP Methods 4Chi-square tests, K-S test, Rank-sum tests, Kruskal Wallis Rank Test, Runs test and Sign testRevisit Breakdowns on vacation

Total No. of Sessions 20