Through clear, step-by-step mathematical calculations, Applied Statistical Inference with MINITAB enables students to gain a solid understanding of how to apply statistical techniques using a statistical software program. It focuses on the concepts of confidence intervals, hypothesis testing, validating model assumptions, and power analysis.


Illustrates the techniques and methods using MINITAB
After introducing some common terminology, the author explains how to create simple graphs using MINITAB and how to calculate descriptive statistics using both traditional hand computations and MINITAB. She then delves into statistical inference topics, such as confidence intervals and hypothesis testing, as well as linear regression, including the Ryan-Joiner test. Moving on to multiple regression analysis, the text addresses ANOVA, the issue of multicollinearity, assessing outliers, and more. It also provides a conceptual introduction to basic experimental design and one-way ANOVA. The final chapter discusses two-way ANOVA, nonparametric analyses, and time series analysis.


Establishes a foundation for studying more complex topics
Ideal for students in the social sciences, this text shows how to implement basic inferential techniques in practice using MINITAB. It establishes the foundation for students to build on work in more advanced inferential statistics.

Series edited by: William R. Schucany, Edward G. Schilling