1 The Nature of Statistical Inference

1．Inferences and Their Accuracy

2．Some Definitions of Terms

3．The Basis for Inferences

4．Types of Inferences

5．The Precision of Inferences

2 The Objective of a Sampling Experiment

1．The Importance of Operational Definitions

2．Defining the Observational Unit

3．Defining the One or More Populations

4．Defining the Population Parameter

5．Defining the Type of Inference

6．Defining the Precision in Inferences

3 The Variability Among Observations

1．Procedure for Estimating Variability

2．Designs for Reducing Variability

3．Stratified Random Sampling

4．Blocking Designs

5．Estimating the Components of Sampling Error

6．Estimating Variability Using a Double Sampling Procedure

4 The Power-Function Approach

1．Estimation Problems

2．Tests of Hypotheses

3．Selection Problems

4．Stating the Precision Desired in an Inference

5 Estimation Problems

1．Confidence Interval for Normal Means

2．Confidence Interval for Difference Between Two Nor-mal Means with Two Independent Samples from Populations with a Common Variance

3．Confidence Interval for Difference Between Two Nor-mal Means with Two Independent Samples from Populations with Unequal Variances

4．Confidence Interval for the Mean Difference Between Paired Observations from a Bivariate Normal Distri-bution

5．Confidence Interval for Any One of Several Normal Means with Independent Samples from Populations with a Common Variance

6．Confidence Interval for Difference Between Any Pair of Several Normal Means with Independent Samples from Populations with a Common Variance

7．Confidence Interval for Any Contrast Among Several Normal Means with Independent Samples from Pop-ulations with a Common Variance

8．Confidence Interval for Normal Variances

9．Confidence Interval for the Ratio of Two Normal Variances

10．Confidence Intervals for Binomial Proportions

11．Confidence Interval for Exponential Scale Parameters

12．Confidence Interval for the Ratio of Two Exponential Scale Parameters

13．Upper Bound on Confidence Interval for Means When Variance is Known

14．Tolerance Limits for the Percentile Range of a Variable

15．Confidence Band for Cumulative Distribution Func-tions

6 Test of Hypotheses

1．Tests of Hypotheses About Normal Means

2．Tests of Hypotheses About Difference Between Two Normal Means with Two Independent Samples from Populations with a Common Variance

3．Tests of Hypotheses About Difference Between Two Normal Means With Two Independent Samples from Populations with Unequal Variances

4．Tests of Hypotheses About the Mean Difference Be-tween Paired Observations from a Bivariate Normal Distribution

5．Tests of Hypotheses About the Equality of Several Normal Means with Independent Samples from Pop-ulations with a Common Variance

6．Tests of Hypotheses About Normal Variances

7．Tests of Hypotheses About the Ratio of Two Normal Variances

8．Tests of Hypotheses About Binomial Proportions

9．Tests of Hypotheses About the Equality of Two Bi-nomial Proportions

10．Tests of Hypotheses About the Equality of Several Binomial Proportions

11．Tests of Hypotheses About Exponential Scale Pa-rameters

12．Tests of Hypotheses About the Ratio of Two Expo-nential Scale Parameters

7 Selection Problems

1．Selecting the Best of Several Normal Means with Independent Samples from Populations with a Com-mon Variance

2．Selecting the Best of Several Normal Variances

3．Selecting the Best of Several Binomial Proportions

4．Selecting the Best of Several Exponential Scale Pa-rameters

8 Sequential Sampling

1．Sequential Tests of Hypotheses About Normal Means

2．Sequential Tests of Hypotheses About Normal Vari-ances

3．Sequential Tests of Hypotheses About Binomial Pro-portions

4．Sequential Tests of Hypotheses About Exponential Scale Parameters

9 Lot Acceptance Sampling Plans

1．Military Standard 105 C

2．Military Standard 414

10 Sample-Size Precision Schedules

1．Case Example:An Estimation Problem

2．Case Example:A Test of Hypothesis

3．Case Example:A Selection Problem

11 Decision-Function Approach

1．Estimating a Mean with Losses Proportional to the Square of the Error in the Estimate

2．Estimating a Normal Mean with Losses Proportional to the Absolute Value of the Error in the Estimate

3．Selecting the Best of Several Normal Means with In-dependent Samples from Populations with a Com-mon Variance

4．Selecting the Better of Two Binomial Proportions

5．Testing a Hypothesis About a Normal Mean with Loss from Acceptance and Loss from Rejection Linear Functions of the True but Unknown Population Mean

6．Testing a Hypothesis About a Binomial Proportion with Loss from Acceptance and Loss from Rejection Linear Functions of the True but Unknown Binomial Proportion

References

Appendix Tables

TABLE 1．Upper Percentage Points of the t Distribution

TABLE 2．Upper Percentage Points of the x2 Distribu-tion

TABLE 3．Upper 10 Percentage Points of the F Distri-bution

TABLE 4．Upper 5 Percentage Points of the F Distri-bution

TABLE 5．Upper 1 Percentage Points of the F Distri-bution

TABLE 6．Upper Percentage Points of the Noncentral t Distribution when the Probability of Erroneously Reject-ing the Test Hypothesis(α)Equals 0．05

TABLE 7．Upper Percentage Points of the Noncentral t Distribution when the Probability of Erroneously Reject-ing the Test Hypothesis(α)Equals 0．01

TABLE 8．Upper Percentage Points of the Noncentral x2 Distribution when the Probability of Erroneously Re-jecting the Test Hypothesis(α)Equals 0．05

TABLE 9．Upper Percentage Points of the Noncentral x2 Distribution when the Probability of Erroneously Re-jecting the Test Hypothesis(α)Equals 0．01

TABLE 10．Upper 20 Percentage Points of the Ф Func-tion when the Probability of Erroneously Rejecting the Test Hypothesis(α)Equals 0．05

TABLE 11．Upper 20 Percentage Points of the Ф Func-tion when the Probability of Erroneously Rejecting the Test Hypothesis(α)Equals 0．01

TABLE 12．Upper 30 Percentage Points of the Ф Func-tion when the Probability of Erroneously Rejecting the Test Hypothesis(α)Equals 0．05

TABLE 13．Upper 30 Percentage Points of the Ф Func-tion when the Probability of Erroneously Rejecting the Test Hypothesis(α)Equals 0．01

TABLE 14．Upper 5 Percentage Points of the Multi-variate t Distribution with Correlations Plus One Half

TABLE 15．Upper 1 Percentage Points of the Multi-variate t Distribution with Correlations Plus One Half

TABLE 16．Upper 10 Percentage Points of the Student-ized Range,(xn－x1)/s

TABLE 17．Upper 5 Percentage Points of the Student-ized Range,(xn－x1)/s

TABLE 18．Upper 1 Percentage Points of the Student-ized Range,(xn－x1)/s

TABLE 19．Upper Percentage Points of d(n,the Maxi-mum Absolute Difference Between Sample and Popula-tion Cumulative Distributions

TABLE 20．y=2 arcsin ？

Index