# Quality Engineering Statistics

ASQ Quality Press, Jan 1, 1992 - Technology & Engineering - 111 pages
This book is a compendium of many of the statistical tools and tests used by quality and engineering professionals. it is a practical handbook that lists significant statistical methods, outlines assumptions for testing, and provides formulas and completed examples. the book is ideal for engineers who know what type of test to perform but need an easy-to-use reference to help complete the task. Readers should have an understanding of basic statistics. a bibliography contains references to texts that can provide the necessary theory and mathematical foundations.

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### Contents

 Point Estimates i 12 Estimates of Dispersion v 14 Measure of Dispersion for Attribute Data vii Confident Intervals ix 22 Confidence Interval for the Variance x 23 Confidence Interval for Fraction Nonconforming Normal Distribution 11 24 Confidence Interval for Proportion 12 25 Small Sample Size Confidence Intervals 13
 72 Poisson Distribution 53 73 Hypergeometric Distribution 55 74 Geometric Distribution 56 75 Uniform Distribution 57 76 Negative Binomial Distribution 58 GoodnessofFit Tests 61 82 Test of Normality Using Skewness and Kurtosis 63 Sample Size Determination for Tests of Hypotheses 67

 26 Confidence Interval for Poisson Distributed Data 14 Testing for Differences in Means 17 32 OneSided Test 𝜎 Known 18 33 Testing a Sample Mean Versus a Hypothesized Mean When 𝜎 Is Estimated From the Sample Data One Sample t Test 19 34 Testing for a Difference in Two Population Means Standard Deviations Known Two Sample Z Test 20 35 Testing for a Difference in Two Population Means Standard Deviations Not Known But Assumed Equal Two Sample t Test 21 36 Testing for a Difference in Two population Means Standard Deviations Not Known and Not Assumed Equal AspinWelch Test 22 37 Testing for Differences in Means of Paired Samples Paired Sample t Test 23 38 Testing for a Difference in Two Proportions 25 39 Testing for Difference in Count Data 26 310 Hypothesis Testing for Differences in Means Confidence Interval Approach 27 Testing for Differences in Variances 31 42 Testing an Observed Variance to a Hypothesized Variance Large Samples 32 43 Testing for a Difference in Two Observed Variances Using Sample Data F Test 33 44 Testing for a Difference in Two Observed Variances Using Large Samples 34 45 Testing for Differences in Several Observed Variances Bartletts Test 35 Decision Errors and Risks in Hypothesis Testing 39 52 Alpha 𝛼 and Beta 𝛽 Risks 40 Continuous Probability Distributions 43 62 Predictions Using the Normal Distribution 44 63 Central Limit Theorem 45 65 Lognormal Distribution 49 Discrete Probability Distributions 51
 91 Sample Size Required to Test an Observed Mean Versus a Hypothesized Mean When 𝜎 Is Known One Sample Z Test 68 92 Sample Size Required to Test an Observed Mean Versus a Hypothesized Mean When 𝜎 Is Estimated From Observed Values One Sample t Test 69 93 Sample Size Required to Test for Differences in Two Observed Means When Each Population Is Known Two Sample Z Test 70 94 Sample Size Required to Test for Differences in Two Observed Means When 𝜎 Is Estimated From the Observed Data Two Sample t Tests 71 96 Sample Size Required for ChiSquare Test of Observed Variance to a Hypothesized Variance 73 97 Sample Size Required for F Test of Two Observed Variances 74 Analysis of Variance 77 102 OneWay ANOVA Fixed Effects Model 78 103 TwoWay ANOVA Fixed Effects Model Single Replicate 80 104 TwoWay ANOVA Fixed Effects Model With Replication 84 105 Random effects Model 88 Tables 91 Normal Distribution 92 t Distribution 95 ChiSquare 96 F Distribution 𝛼 005 97 F Distribution 𝛼 001 99 Median Rank Values 101 Gamma Function 104 Bibliography 107 Index 109 Copyright