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1.

図書

図書
J.K. Wani
出版情報: New York : Appleton-Century-Crofts, 1971  xiv, 315 p. ; 24 cm
シリーズ名: The Appleton-Century statistics series
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2.

図書

図書
[by] H. G. Cuming [and] C. J. Anson
出版情報: London : Heywood Books, 1966  490 p. ; 26 cm
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3.

図書

図書
Achintya Haldar, Sankaran Mahadevan
出版情報: New York ; Chichester : Wiley, c2000  xvi, 304 p. ; 25 cm
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目次情報: 続きを見る
Basic Concept of Reliability
Mathematics of Probability
Modeling of Uncertainty
Commonly Used Probability Distributions
Determination of Distributions and Parameters from Observed Data
Randomness in Response Variables
Fundamentals of Reliability Analysis
Advanced Topics on Reliability Analysis
Simulation Techniques
Appendices
Conversion Factors
References
Index
Basic Concept of Reliability
Mathematics of Probability
Modeling of Uncertainty
4.

図書

図書
by Robert M. Kozelka
出版情報: Reading, Mass. : Addison-Wesley Pub. Co, c1961  x, 150 p ; 24 cm
シリーズ名: Addison-Wesley series in statistics
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5.

図書

図書
Arnold O. Allen
出版情報: New York : Academic Press, 1978  xvi, 390 p. ; 24 cm
シリーズ名: Computer science and applied mathematics
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6.

図書

図書
Narayan C. Giri
出版情報: New York : M. Dekker, 1974  viii, 260 p. ; 24 cm
シリーズ名: Statistics : textbooks and monographs ; v. 7 . Introduction to probability and statistics ; pt. 1
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7.

図書

図書
Narayan C. Giri
出版情報: New York : M. Dekker, c1975  viii, 314 p. ; 24 cm
シリーズ名: Statistics : textbooks and monographs ; v. 7 . Introduction to probability and statistics ; pt. 2
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8.

図書

図書
[by] V. V. Bolotin. Translated by Samuel Aroni
出版情報: San Francisco : Holden-Day, [1969]  xix, 240 p. ; 24 cm
シリーズ名: Holden-Day series in mathematical physics
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9.

図書

図書
William Mendenhall
出版情報: Boston : Duxbury Press, c1987  xvi, 783, 100 p. ; 25 cm
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目次情報: 続きを見る
Introduction: An Invitation to Statistics
The Population and the Sample
Descriptive and Inferential Statistics
Achieving the Objective of Inferential Statistics: The Necessary Steps
Describing Data with Graphs / 1:
Variables and Data / 1.1:
Types of Variables / 1.2:
Graphs for Categorical Data / 1.3:
Graphs for Quantitative Data / 1.4:
Relative Frequency Histograms / 1.5:
Describing Data with Numerical Measures / 2:
Describing a Set of Data with Numerical Measures / 2.1:
Measures of Center / 2.2:
Measures of Variability / 2.3:
On the Practical Significance of the Standard Deviation / 2.4:
A Check on the Calculation of s / 2.5:
Measures of Relative Standing / 2.6:
The Five-Number Summary and the Box Plot / 2.7:
Describing Bivariate Data / 3:
Bivariate Data / 3.1:
Graphs for Qualitative Variables / 3.2:
Scatterplots for Two Quantitative Variables / 3.3:
Numerical Measures for Quantitative Bivariate Data / 3.4:
Probability and Probability Distributions / 4:
The Role of Probability in Statistics / 4.1:
Events and the Sample Space / 4.2:
Calculating Probabilities Using Simple Events / 4.3:
Useful Counting Rules (Optional) / 4.4:
Event Relations and Probability Rules / 4.5:
Conditional Probability, Independence, and the Multiplicative Rule / 4.6:
Bayes' Rule (Optional) / 4.7:
Discrete Random Variables and Their Probability Distributions / 4.8:
Several Useful Discrete Distributions / 5:
Introduction / 5.1:
The Binomial Probability Distribution / 5.2:
The Poisson Probability Distribution / 5.3:
The Hypergeometric Probability Distribution / 5.4:
The Normal Probability Distribution / 6:
Probability Distributions for Continuous Random Variables / 6.1:
Tabulated Areas of the Normal Probability Distribution / 6.2:
The Normal Approximation to the Binomial Probability Distribution (Optional) / 6.4:
Sampling Distributions / 7:
Sampling Plans and Experimental Designs / 7.1:
Statistics and Sampling Distributions / 7.3:
The Central Limit Theorem / 7.4:
The Sampling Distribution of the Sample Mean / 7.5:
The Sampling Distribution of the Sample Proportion / 7.6:
A Sampling Application: Statistical Process Control (Optional) / 7.7:
Large-Sample Estimation / 8:
Where We've Been / 8.1:
Where We're Going--Statistical Inference / 8.2:
Types of Estimators / 8.3:
Point Estimation / 8.4:
Interval Estimation / 8.5:
Estimating the Difference between Two Population Means / 8.6:
Estimating the Difference between Two Binomial Proportions / 8.7:
One-Sided Confidence Bounds / 8.8:
Choosing the Sample Size / 8.9:
Large-Sample Tests of Hypotheses / 9:
Testing Hypotheses about Population Parameters / 9.1:
A Statistical Test of Hypothesis / 9.2:
A Large-Sample Test about a Population Mean / 9.3:
A Large-Sample Test of Hypothesis for the Difference between Two Population Means / 9.4:
A Large-Sample Test of Hypothesis for a Binomial Proportion / 9.5:
A Large-Sample Test of Hypothesis for the Difference between Two Binomial Proportions / 9.6:
Some Comments on Testing Hypotheses / 9.7:
Inference from Small Samples / 10:
Student's t Distribution / 10.1:
Small-Sample Inferences Concerning a Population Mean / 10.3:
Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samples / 10.4:
Small-Sample Inferences for the Difference between Two Means: A Paired-Difference Test / 10.5:
Inferences Concerning a Population Variance / 10.6:
Comparing Two Population Variances / 10.7:
Revisiting the Small-Sample Assumptions / 10.8:
The Analysis of Variance / 11:
The Design of an Experiment / 11.1:
What Is an Analysis of Variance? / 11.2:
The Assumptions for an Analysis of Variance / 11.3:
The Completely Randomized Design: A One-Way Classification / 11.4:
The Analysis of Variance for a Completely Randomized Design / 11.5:
Ranking Population Means / 11.6:
The Randomized Block Design: A Two-Way Classification / 11.7:
The Analysis of Variance for a Randomized Block Design / 11.8:
The a x b Factorial Experiment: A Two-Way Classification / 11.9:
The Analysis of Variance for an a x b Factorial Experiment / 11.10:
Revisiting the Analysis of Variance Assumptions / 11.11:
A Brief Summary / 11.12:
Linear Regression and Correlation / 12:
A Simple Linear Probabilistic Model / 12.1:
The Method of Least Squares / 12.3:
An Analysis of Variance for Linear Regression / 12.4:
Testing the Usefulness of the Linear Regression Model / 12.5:
Diagnostic Tools for Checking the Regression Assumptions / 12.6:
Estimation and Prediction Using the Fitted Line / 12.7:
Correlation Analysis / 12.8:
Multiple Regression Analysis / 13:
The Multiple Regression Model / 13.1:
A Multiple Regression Analysis / 13.3:
A Polynomial Regression Model / 13.4:
Using Quantitative and Qualitative Predictor Variables in a Regression Model / 13.5:
Testing Sets of Regression Coefficients / 13.6:
Interpreting Residual Plots / 13.7:
Stepwise Regression Analysis / 13.8:
Misinterpreting a Regression Analysis / 13.9:
Steps to Follow When Building a Multiple Regression Model / 13.10:
Analysis of Categorical Data / 14:
A Description of the Experiment / 14.1:
Pearson's Chi-Square Statistic / 14.2:
Testing Specified Cell Probabilities: The Goodness-of-Fit Test / 14.3:
Contingency Tables: A Two-Way Classification / 14.4:
Comparing Several Multinomial Populations: A Two-Way Classification with Fixed Row or Column Totals / 14.5:
The Equivalence of Statistical Tests / 14.6:
Other Applications of the Chi-Square Test / 14.7:
Nonparametric Statistics / 15:
The Wilcoxon Rank Sum Test: Independent Random Samples / 15.1:
The Sign Test for a Paired Experiment / 15.3:
A Comparison of Statistical Tests / 15.4:
The Wilcoxon Signed-Rank Test for a Paired Experiment / 15.5:
The Kruskal-Wallis H Test for Completely Randomized Designs / 15.6:
The Friedman F[subscript r] Test for Randomized Block Designs / 15.7:
Rank Correlation Coefficient / 15.8:
Summary / 15.9:
Appendix I
Cumulative Binomial Probabilities / Table 1:
Cumulative Poisson Probabilities / Table 2:
Areas under the Normal Curve / Table 3:
Critical Values of t / Table 4:
Critical Values of Chi-Square / Table 5:
Percentage Points of the F Distribution / Table 6:
Critical Values of T for the Wilcoxon Rank Sum Test, n[subscript 1] [less than or equal] n[subscript 2] / Table 7:
Critical Values of T for the Wilcoxon Signed-Rank Test, n = 5(1)50 / Table 8:
Critical Values of Spearman's Rank Correlation Coefficient for a One-Tailed Test / Table 9:
Random Numbers / Table 10:
Percentage Points of the Studentized Range, q[subscript [alpha](k, df) / Table 11:
Answers to Selected Exercises
Index
Credits
Introduction: An Invitation to Statistics
The Population and the Sample
Descriptive and Inferential Statistics
10.

図書

図書
R. Dobrushin, P. Groeneboom, M. Ledoux ; editor, P. Bernard
出版情報: Berlin ; Tokyo : Springer-Verlag, c1996  viii, 300 p. ; 24 cm
シリーズ名: Lecture notes in mathematics ; 1648
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