Course Description

Statistics is the art of using data to make numerical conjectures about problems. Descriptive statistics is the art of summarizing data. Topics include histograms, the average, the standard deviation, the normal curve, correlation. Much statistical reasoning depends on the theory of probability. Topics include chance models, expected value, standard error, probability histograms, convergence to the normal curve. Statistical inference is the art of making valid generalizations from samples. Topics include estimation, measurement error, tests of statistical significance Descriptive statistics will teach you the basic concepts used to describe data. This is a great beginner course for those interested in Data Science, Economics, Psychology, Machine Learning, Sports analytics, and just about any other field.

Further description

This is an introductory course in statistics designed to provide students with the basic concepts of data analysis and statistical computing . Topics covered include basic descriptive measures, measures of association, probability theory, confidence intervals, and hypothesis testing. The main objective is to provide students with pragmatic tools for assessing statistical claims and conducting their own statistical analyses.

Course Learning Objectives (CLO)

At the end of this course, students should be able to:

In terms of knowledge:

➢ Demonstrate their understanding of descriptive statistics by practical application of quantitative reasoning and data visualization

➢ Demonstrate their knowledge of the basics of inferential statistics by making valid generalizations from sample data

In terms of skills:

➢ Recognize pitfalls i n using statistical methodology In terms of attitudes , students should develop in this course :

➢ Critical attitudes, which are necessary for “life long learning”

➢ Greater appreciation for the importance of statistical literacy in today’s data rich world

Recommended References books

Freedman, David, Robert Pisani, & Roger Pervis ( Statistics New York: W. W. Norton James, Gareth, Daniela Witten , Trevor Hastie , & Robert Tibshirani ( An Introduction to Statistical Learning: With Applications in R. New York: Springer.

Kabacoff, Robert ( R In Action: Data Analysis and Graphics with R Shelter Island, NY: Manning Publications Co.

Leading Journals in Business Studies

Journal of International Business Studies; Journal of Management Studies ; Journal of Marketing; Academy of Management Review; Accounting, Organizations and Society ; Accounting Review ; Administrative Science Quarterly; American Economic Review ; Contemporary Accounting Research; Econometrica; Entrepreneurship Theory and Practice; Harvard Business Review ; Human Relations ; Human Resource Management; Information Systems Research ; Journal of Accounting and Economics ; Journal of Accounting Research ; Journal of Applied Psychology; Journal of Business Ethics ’ Journal of Business Venturing ; Journal of Consumer Psychology ; Journal of Consumer Research ; Journal of Finance ; Journal of Financial and Quantitative Analysis ; Journal of Financial Economics ; Journal of Management ; Journal of Management Information Systems Journal of Marketing Research Journal of Operations Management ; Journal of Political Economy ; Journal of the Academy of Marketing Science ; Management Science ; Manufacturing & Service Operations Management ; Marketing Science ; MIS Quarterly ; MIT Sloan Management Review ; Operations Research ; Organization Science ; Organization Studies; Organizational Behavior and Human Decision Processes ; Production and Operations Management ; Quarterly Journal of Economics ; Research Policy ; Review of Accounting Studies ; Review of Economic Studies ; Review of Finance ; Review of Financial Studies ; Strategic Entrepreneurship Journal ; Strategic Management Journal