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Introductory statistics for data ana...

Ewens, Warren J.

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Introductory statistics for data analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introductory statistics for data analysis/ by Warren J. Ewens, Katherine Brumberg.
作者:	Ewens, Warren J.
其他作者:	Brumberg, Katherine.
出版者:	Cham :Springer Nature Switzerland : : 2023.,
面頁冊數:	1 online resource (x, 273 p.) :ill., digital ;24 cm.
內容註:	I INTRODUCTION -- 1 Statistics and probability theory -- II PROBABILITY THEORY -- 2 Events -- 3 Probabilities of events -- 4 Probability: One Discrete Random Variable -- 5 Many Random Variables -- 6 Continuous Random Variables -- III STATISTICS -- 7 Introduction -- 8 Estimation of a parameter -- 9 Testing hypotheses about the value of a parameter -- 10 Testing for the equality of two binomial parameters -- 10 Testing for the equality of two binomial parameters -- 11 Chi-square tests (i): tables bigger than two-by-two -- 13 Tests on means -- 14 Non-parametric tests -- Useful charts -- Solutions to problems.
Contained By:	Springer Nature eBook
標題:	Mathematical statistics. -
電子資源:	https://doi.org/10.1007/978-3-031-28189-1
ISBN:	9783031281891

Introductory statistics for data analysis
Ewens, Warren J.

Introductory statistics for data analysis[electronic resource] /by Warren J. Ewens, Katherine Brumberg. - Cham :Springer Nature Switzerland :2023. - 1 online resource (x, 273 p.) :ill., digital ;24 cm.

I INTRODUCTION -- 1 Statistics and probability theory -- II PROBABILITY THEORY -- 2 Events -- 3 Probabilities of events -- 4 Probability: One Discrete Random Variable -- 5 Many Random Variables -- 6 Continuous Random Variables -- III STATISTICS -- 7 Introduction -- 8 Estimation of a parameter -- 9 Testing hypotheses about the value of a parameter -- 10 Testing for the equality of two binomial parameters -- 10 Testing for the equality of two binomial parameters -- 11 Chi-square tests (i): tables bigger than two-by-two -- 13 Tests on means -- 14 Non-parametric tests -- Useful charts -- Solutions to problems.

This book describes the probability theory associated with frequently used statistical procedures and the relation between probability theory and statistical inference. The first third of the book is dedicated to probability theory including topics relating to events, random variables, and the Central Limit Theorem. Statistical topics then include parameter estimation with confidence intervals, hypothesis testing, chi-square tests, t tests, and several non-parametric tests. Flow charts are frequently used to facilitate an understanding of the material considered. The examples and problems in the book all concern simple data sets which can be analyzed with a simple calculator; however, the R code required to complete many examples and problems is provided as well for those that are interested.

ISBN: 9783031281891

Standard No.: 10.1007/978-3-031-28189-1doiSubjects--Topical Terms:

516858
Mathematical statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Introductory statistics for data analysis
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505 0 $a I INTRODUCTION -- 1 Statistics and probability theory -- II PROBABILITY THEORY -- 2 Events -- 3 Probabilities of events -- 4 Probability: One Discrete Random Variable -- 5 Many Random Variables -- 6 Continuous Random Variables -- III STATISTICS -- 7 Introduction -- 8 Estimation of a parameter -- 9 Testing hypotheses about the value of a parameter -- 10 Testing for the equality of two binomial parameters -- 10 Testing for the equality of two binomial parameters -- 11 Chi-square tests (i): tables bigger than two-by-two -- 13 Tests on means -- 14 Non-parametric tests -- Useful charts -- Solutions to problems.
520 $a This book describes the probability theory associated with frequently used statistical procedures and the relation between probability theory and statistical inference. The first third of the book is dedicated to probability theory including topics relating to events, random variables, and the Central Limit Theorem. Statistical topics then include parameter estimation with confidence intervals, hypothesis testing, chi-square tests, t tests, and several non-parametric tests. Flow charts are frequently used to facilitate an understanding of the material considered. The examples and problems in the book all concern simple data sets which can be analyzed with a simple calculator; however, the R code required to complete many examples and problems is provided as well for those that are interested.
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