Details

<p>OTHER CONCEPTS COVERED IN THE ARTICLES xi</p> <p>WHY THIS BOOK IS NEEDED xix</p> <p>WHAT MAKES THIS BOOK UNIQUE? xxiii</p> <p>HOW TO USE THIS BOOK xxv <br /><br />ALPHA, 𝜶 1</p> <p>ALPHA AND BETA ERRORS 9</p> <p>ALPHA, <i>p</i>, CRITICAL VALUE, AND TEST STATISTIC –HOW THEY WORK TOGETHER 14</p> <p>ALTERNATIVE HYPOTHESIS 22</p> <p>ANALYSIS OF MEANS (ANOM) 27</p> <p>ANOVA – PART 1: WHAT IT DOES 32</p> <p>ANOVA – PART 2: HOW IT DOES IT 36</p> <p>ANOVA – PART 3: 1-WAY (AKA SINGLE FACTOR) 42</p> <p>ANOVA – PART 4: 2-WAY (AKA 2-FACTOR) 47</p> <p>ANOVA vs. REGRESSION 54</p> <p>BINOMIAL DISTRIBUTION 62</p> <p>CHARTS/GRAPHS/PLOTS – WHICH TO USE WHEN 69</p> <p>CHI-SQUARE – THE TEST STATISTIC AND ITS DISTRIBUTIONS 76</p> <p>CHI-SQUARE TEST FOR GOODNESS OF FIT 82</p> <p>CHI-SQUARE TEST FOR INDEPENDENCE 89</p> <p>CHI-SQUARE TEST FOR THE VARIANCE 98</p> <p>CONFIDENCE INTERVALS – PART 1: GENERAL CONCEPTS 101</p> <p>CONFIDENCE INTERVALS – PART 2: SOME SPECIFICS 108</p> <p>CONTROL CHARTS – PART 1: GENERAL CONCEPTS AND PRINCIPLES 113</p> <p>CONTROL CHARTS – PART 2: WHICH TO USE WHEN 119</p> <p>CORRELATION – PART 1 124</p> <p>CORRELATION – PART 2 129</p> <p>CRITICAL VALUE 135</p> <p>DEGREES OF FREEDOM 141</p> <p>DESIGN OF EXPERIMENTS (DOE) – PART 1 146</p> <p>DESIGN OF EXPERIMENTS (DOE) – PART 2 151</p> <p>DESIGN OF EXPERIMENTS (DOE) – PART 3 158</p> <p>DISTRIBUTIONS – PART 1: WHAT THEY ARE 165</p> <p>DISTRIBUTIONS – PART 2: HOW THEY ARE USED 171</p> <p>DISTRIBUTIONS – PART 3: WHICH TO USE WHEN 177</p> <p>ERRORS – TYPES, USES, AND INTERRELATIONSHIPS 178</p> <p>EXPONENTIAL DISTRIBUTION 184</p> <p>F 189</p> <p>FAIL TO REJECT THE NULL HYPOTHESIS 195</p> <p>HYPERGEOMETRIC DISTRIBUTION 200</p> <p>HYPOTHESIS TESTING – PART 1: OVERVIEW 202</p> <p>HYPOTHESIS TESTING – PART 2: HOW TO 208</p> <p>INFERENTIAL STATISTICS 212</p> <p>MARGIN OF ERROR 220</p> <p>NONPARAMETRIC 223</p> <p>NORMAL DISTRIBUTION 230</p> <p>NULL HYPOTHESIS 235</p> <p><i>p</i>, <i>p</i>-VALUE 241</p> <p><i>p</i>, <i>t</i>, AND <i>F</i>: “>”OR “<”? 246</p> <p>POISSON DISTRIBUTION 250</p> <p>POWER 254</p> <p>PROCESS CAPABILITY ANALYSIS (PCA) 259</p> <p>PROPORTION 266</p> <p><i>r</i>, MULTIPLE <i>R</i>, <i>r²</i>, <i>R²</i>, <i>R</i> SQUARE, <i>R²</i> ADJUSTED 274</p> <p>REGRESSION – PART 1: SUMS OF SQUARES 277</p> <p>REGRESSION – PART 2: SIMPLE LINEAR 285</p> <p>REGRESSION – PART 3: ANALYSIS BASICS 292</p> <p>REGRESSION – PART 4: MULTIPLE LINEAR 297</p> <p>REGRESSION – PART 5: SIMPLE NONLINEAR 305</p> <p>REJECT THE NULL HYPOTHESIS 311</p> <p>RESIDUALS 315</p> <p>SAMPLE, SAMPLING 320</p> <p>SAMPLE SIZE – PART 1: PROPORTIONS FOR COUNT DATA 326</p> <p>SAMPLE SIZE – PART 2: FOR MEASUREMENT/CONTINUOUS DATA 334</p> <p>SAMPLING DISTRIBUTION 339</p> <p>SIGMA 343</p> <p>SKEW, SKEWNESS 344</p> <p>STANDARD DEVIATION 348</p> <p>STANDARD ERROR 352</p> <p>STATISTICALLY SIGNIFICANT 357</p> <p>SUMS OF SQUARES 363</p> <p><i>t</i> – THE TEST STATISTIC AND ITS DISTRIBUTIONS 364</p> <p><i>t</i>-TESTS – PART 1: OVERVIEW 370</p> <p><i>t</i>-TESTS – PART 2: CALCULATIONS AND ANALYSIS 376</p> <p>TEST STATISTIC 385</p> <p>VARIABLES 392</p> <p>VARIANCE 397</p> <p>VARIATION/VARIABILITY/DISPERSION/SPREAD 404</p> <p>WHICH STATISTICAL TOOL TO USE TO SOLVE SOME COMMON PROBLEMS 408</p> <p>Z 412</p>

<p><b>ANDREW A. JAWLIK </b>received his B.S. in Mathematics and his M.S. in Mathematics and Computer Science from the University of Michigan. He held jobs with IBM in marketing, sales, finance, and information technology, as well as a position as Process Executive. In these jobs, he learned how to communicate difficult technical concepts in easy - to - understand terms. He completed Lean Six Sigma Black Belt coursework at the IASSC - accredited Pyzdek Institute. In order to understand the confusing statistics involved, he wrote explanations in his own words and graphics. Using this material, he passed the certification exam with a perfect score. Those statistical explanations then became the starting point for this book.</p>

<p><b>Statistics is confusing, even for smart, technically competent people. </b>And many students and professionals find that existing books and web resources don’t give them an intuitive understanding of confusing statistical concepts. That is why this book is needed. Some of the unique qualities of this book are:</p> <p>• <b>Easy to Understand: </b>Uses unique “graphics that teach” such as concept flow diagrams, compare-and-contrast tables, and even cartoons to enhance “rememberability.”</p> <p>• <b>Easy to Use: </b>Alphabetically arranged, like a mini-encyclopedia, for easy lookup on the job, while studying, or during an open-book exam.</p> <p>• <b>Wider Scope: </b>Covers Statistics I and Statistics II and Six Sigma Black Belt, adding such topics as control charts and statistical process control, process capability analysis, and design of experiments. As a result, this book will be useful for business professionals and industrial engineers in addition to students and professionals in the social and physical sciences.</p> <p>In addition, each of the 60+ concepts is covered in one or more articles. The 75 articles in the book are usually 5–7 pages long, ensuring that things are presented in “bite-sized chunks.” The first page of each article typically lists five “Keys to Understanding” which tell the reader everything they need to know on one page. This book also contains an article on “Which Statistical Tool to Use to Solve Some Common Problems”, additional “Which to Use When” articles on Control Charts, Distributions, and Charts/Graphs/Plots, as well as articles explaining how different concepts work together (e.g., how Alpha, <i>p</i>, Critical Value, and Test Statistic interrelate).</p>

US