MINITAB Manual For Introduction ToThe Practice of Statistics

1 MINITAB Manual For David Moore and George McCabe's Introduction To The Practice of Statistics Michael Evans University of Toronto ii Contents Preface vii I MINITAB for Data Management 1. 1 Manual Overview and Conventions .. 3. 2 Accessing and Exiting MINITAB .. 4. 3 Files Used by MINITAB .. 6. 4 Getting Help .. 7. 5 The Worksheet .. 7. 6 MINITAB Commands .. 9. 7 Entering Data into a Worksheet .. 12. Importing Data .. 13. Patterned Data .. 17. Printing Data in the Session Window .. 18. Assigning Constants .. 19. Naming Variables and Constants .. 20. Information about a Worksheet .. 21. Editing a Worksheet.

2 21. 8 Saving, Retrieving, and Printing .. 24. 9 Mathematical Operations .. 27. Arithmetical Operations .. 27. Mathematical Functions .. 28. Comparisons and Logical Operations .. 29. Column and Row Statistics .. 31. Sorting Data .. 33. Computing Ranks .. 34. 10 Exercises .. 35. II MINITAB for Data Analysis 37. 1 Looking at Data Distributions 39. Tabulating and Summarizing Data .. 40. Tallying Data .. 41. iii iv CONTENTS. Describing Data .. 43. Plotting Data .. 45. Stem-and-Leaf Plots .. 45. Histograms .. 46. Boxplots .. 51. Bar Charts .. 53. Pie Charts .. 55. Time Series Plots .. 56. The Normal Distribution.

3 58. Calculating the Density .. 58. Calculating the Distribution Function .. 59. Calculating the Inverse Distribution Function .. 60. Normal Probability Plots .. 60. Exercises .. 63. 2 Looking at Data Relationships 65. Scatterplots .. 65. Correlations .. 69. Regression .. 69. Transformations .. 73. Exercises .. 74. 3 Producing Data 77. Generating a Random Sample .. 78. Sampling from Distributions .. 80. Exercises .. 82. 4 Probability: The Study of Randomness 85. Basic Probability Calculations .. 85. More on Sampling from Distributions .. 87. Simulation for Approximating Probabilities .. 90. Simulation for Approximating Means.

4 91. Exercises .. 91. 5 Sampling Distributions 95. The Binomial Distribution .. 95. Simulating Sampling Distributions .. 98. Exercises .. 101. 6 Introduction to Inference 105. z Con dence Intervals .. 105. z Tests .. 106. Simulations for Con dence Intervals .. 108. Power Calculations .. 110. The Chi-Square Distribution .. 112. Exercises .. 113. CONTENTS v 7 Inference for Distributions 115. The Student Distribution .. 115. t Con dence Intervals .. 116. t Tests .. 117. The Sign Test .. 118. Comparing Two Samples .. 120. The F Distribution .. 122. Exercises .. 124. 8 Inference for Proportions 127. Inference for a Single Proportion.

5 127. Inference for Two Proportions .. 130. Exercises .. 132. 9 Inference for Two-Way Tables 133. Tabulating and Plotting .. 133. The Chi-square Test .. 138. Analyzing Tables of Counts .. 140. Exercises .. 142. 10 Inference for Regression 145. Simple Regression Analysis .. 145. Exercises .. 153. 11 Multiple Regression 155. Example of a Multiple Regression .. 155. Exercises .. 160. 12 One-Way Analysis of Variance 163. A Categorical Variable and a Quantitative Variable .. 163. One-Way Analysis of Variance .. 167. Exercises .. 172. 13 Two-Way Analysis of Variance 175. The Two-Way ANOVA Command .. 175.

6 Exercises .. 179. 14 Bootstrap Methods and Permutation Tests 181. Bootstrap Sampling .. 182. Permutation Tests .. 185. Exercises .. 189. 15 Nonparametric Tests 191. The Wilcoxon Rank Sum Procedures .. 191. The Wilcoxon Signed Rank Procedures .. 193. The Kruskal-Wallis Test .. 194. Exercises .. 195. vi CONTENTS. 16 Logistic Regression 197. The Logistic Regression Model .. 197. Example .. 198. Exercises .. 200. 17 Statistics for Quality: Control and Capability 203. Producing x Charts .. 203. Producing S Charts .. 207. Producing p Charts .. 208. Exercises .. 210. A Projects 213. B Functions in MINITAB 215.

7 Mathematical Functions .. 215. Column Statistics .. 216. Row Statistics .. 217. C More MINITAB Commands 219. Coding .. 219. Concatenating Columns .. 220. Converting Data Types .. 221. History .. 222. Stacking and Unstacking Columns .. 223. D Programming in MINITAB 225. Global Macros .. 225. Control Statements .. 226. Startup Macro .. 230. Interactive Macros .. 230. Local Macros .. 231. E Matrix Algebra in MINITAB 233. Creating Matrices .. 234. Commands for Matrix Operations .. 238. Index 243. Preface This MINITAB Manual is to be used as an accompaniment to Introduction to the Practice of Statistics , Fifth Edition, by David S.

8 Moore and George P. McCabe, and to the CD-ROM that accompanies this text. We abbreviate the textbook title as IPS. It can be used with either MINITAB Student Version 14, MINITAB Version 14 or MINITAB Version 13 running under Windows. The text is based on MINITAB Student Version 14 and MINITAB Version 14, but we have also indicated in the Manual wherever there are di erences with MINITAB Version 13, in the way these versions work. The core of the Manual is a discussion of the menu commands while not neglecting to refer to the session commands, as these are needed for certain problems. The material on session commands is always at the end of each section and can be skipped if the reader will de nitely not be using them.

9 We have provided some Exercises for each chapter. MINITAB is a statistical software package that was designed especially for the teaching of introductory Statistics courses. It is our view that an easy-to-use statistical software package is a vital and signi cant component of such a course. This permits the student to focus on statistical concepts and thinking rather than computations or the learning of a statistical package. The main aim of any introductory Statistics course should always be the why of Statistics rather than technical details that do little to stimulate the majority of students or, in our opinion, do little to reinforce the key concepts.

10 IPS succeeds admirably in communicating the important basic foundations of statistical thinking, and it is hoped that this Manual serves as a useful adjunct to the text. It is natural to ask why MINITAB is advocated for the course. In the author's experience, ease of learning and use are the salient features of the package, with obvious bene ts to the student and to the instructor, who can relegate many details to the software . While more sophisticated packages are necessary for higher-level professional work, it is our experience that attempting to teach one of these in a course forces too much attention on technical aspects.