Business statistics is the science of good decision making in the face of uncertainty and is used in many disciplines such as financial analysis, econometrics, auditing, production and operations including services improvement, and marketing research.
The aim of the course is to develop competency and ability to use statistical techniques in conducting research and project work. The emphasis of the course is more on interpretation of results and understanding of the strengths and limitations of different statistical measures.
This course has a business focus. The course covers fundamentals of descriptive and inferential statistical techniques. The contents include data summaries and descriptive statistics; introduction to a statistical computer package; Probability: distributions, expectation, variance, covariance, statistical inference of univariateand bivariate data for hypothesis testing.
By the end of this course students would be able tounderstand and use the descriptive and inferential statistical tools used in business decision making ,select an appropriate graph to describe a distribution,calculate and interpret the shape, center and spread of a distribution,understand the problem of inference when working with the results from random samples, andanalyze the data using excel.
Unit I Introduction 5 hours
Basic concepts of statistics, Terminologies associated with statistics such as populations and samples, Variables (Dependent and independent only) , Types and sources of data , Descriptive and inferential statistics, Data processing (editing and coding), Applications of statistics in business and management.
Unit II Describing Data: Graphs and Tables 6 hours
Data array, Stem and leaf Display, Frequency tables, Histograms, Polygon, Cumulative Polygon, Scatter plots, Simple Bar and Pie charts, Cross tabulation
Unit III Describing Data: Summary Measures 10 hours
Central Location: Mean, Median and Mode
Non Central Location: Quartiles, Deciles and Percentiles
Dispersion: Range, Interquartile range, Variance, Standard deviation, Coefficient of variation, Index for qualitative variation (IQV)
Shape: Crude measure (comparison of mean, median, and mode), Five number summary, Box plot
Inequality Measure: Gini concentration ratio
Unit IV Basics of Probability Theory 5 hours
Basic concepts, Counting rule, Objective and subjective probability, Marginal and joint probability, Addition rule, Conditional probability, Multiplication rules.
Unit V Probability Distributions 10 hours
Discrete probability distribution (Binomial and Poisson distribution and mean and standard deviation of their distributions), Continuous probability distribution: Normal distribution, Normal approximation of Binomial and Poisson distribution
Unit VI Estimation and Hypothesis Testing 12 hours
Concept of estimation, Confidence intervals, confidence intervals for means and proportions (one sample case only ), Test of significance, p-value approach to hypothesis testing, connection between confidence intervals and hypothesis testing, comparing two means (two sample z and t- test procedures), and comparing two proportions.
Davis, G., & Pecar, B. Business Statistics using Excel. New Delhi: Oxford University Press
Berenson, M. L. & David M. L. Basic Business Statistics: Concepts and Applications. Upper Saddle River, New Jersey: Pearson Prentice Hall of USA.
Levin, R. I., & David S. R. Statistics for Management. New Delhi: Prentice Hall of India
Allbright, S. C., Winston, W., & Zappe, C. J. Data Analysis and Decision Making with Microsoft Excel. Pacific Grove: Duxubury Press.
Argyrous, G. Statistics for Research with a Guide to SPSS . New Delhi: Sage South India Edition
Whigham, D. Business Data Analysis using Excel. New Delhi: Oxford University Press