Applied Statistics for Business and Economics
Designed for a one-semester course, Applied Statistics for Business and Economics offers students in business and the social sciences an effective introduction to some of the most basic and powerful techniques available for understanding their world. Numerous interesting and important examples reflect real-life situations, stimulating students to think realistically in tackling these problems. Calculations can be performed using any standard spreadsheet package. To help with the examples, the author offers both actual and hypothetical databases on his website http://iwu.edu/~bleekley
The text explores ways to describe data and the relationships found in data. It covers basic probability tools, Bayes’ theorem, sampling, estimation, and confidence intervals. The text also discusses hypothesis testing for one and two samples, contingency tables, goodness-of-fit, analysis of variance, and population variances. In addition, the author develops the concepts behind the linear relationship between two numeric variables (simple regression) as well as the potentially nonlinear relationships among more than two variables (multiple regression). The final chapter introduces classical time-series analysis and how it applies to business and economics.
This text provides a practical understanding of the value of statistics in the real world. After reading the book, students will be able to summarize data in insightful ways using charts, graphs, and summary statistics as well as make inferences from samples, especially about relationships.
Introduction to Statistics. Describing Data: Tables and Graphs. Describing Data: Summary Statistics. Basic Probability. Probability Distributions. Sampling and Sampling Distributions. Estimation and Confidence Intervals. Tests of Hypotheses: One-Sample Tests. Tests of Hypotheses: Two-Sample Tests. Tests of Hypotheses: Contingency and Goodness-of-Fit. Tests of Hypotheses: ANOVA and Tests of Variances. Simple Regression and Correlation. Multiple Regression. Time-Series Analysis. Appendices. Index.