Understanding inferential statistics from a for significance test to z for confidence interval /
What actually is a p-value for? And what is a significant result? This book answers such questions by providing a compact introduction to inferential statistics. Our major focus is on the logic of inferential statistics and hypothesis testing: We cover the logic behind statistical tests, we then wal...
| Main Author: | Janczyk, Markus. |
|---|---|
| Other Authors: | Pfister, Roland, 1949-, SpringerLink (Online service) |
| Format: | eBook |
| Language: | English German |
| Published: |
Berlin :
Springer,
2023.
Berlin : 2023. |
| Physical Description: |
1 online resource. |
| Subjects: |
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| 245 | 1 | 0 | |a Understanding inferential statistics : |b from a for significance test to z for confidence interval / |c Markus Janczyk, Roland Pfister. |
| 260 | |a Berlin : |b Springer, |c 2023. | ||
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| 505 | 0 | |a Introduction and descriptive statistics -- Basics of inferential statistics 1: random variables -- Basics of inferential statistics 2: population and parameter estimation -- Hypothesis testing and significance -- Difference hypotheses with a maximum of two groups: t-tests. Confidence intervals -- Error types, effect size and power -- Single factor analysis of variance -- Multifactorial analysis of variance -- Analysis of variance with repeated measures -- Correlation hypotheses: Correlation and regression -- Concluding remarks. | |
| 520 | |a What actually is a p-value for? And what is a significant result? This book answers such questions by providing a compact introduction to inferential statistics. Our major focus is on the logic of inferential statistics and hypothesis testing: We cover the logic behind statistical tests, we then walk through the most common procedures (t-test, analysis of variance with and without repeated measures, correlation/regression) and discuss pitfalls of data analysis. The book thus helps developing a solid understanding of how common test procedures work, and how to interpret their results correctly. Hands-on examples from everyday research including exemplary calculations with the programs SPSS and R supplement each chapter. In addition to classical methods, we briefly discuss recent developments in psychological research methods. This book is a translation of the original German 3rd edition of Inferenzstatistik Verstehen by Markus Janczyk and Roland Pfister. It is based on an AI-powered machine translation (by the service DeepL.com), with thorough follow-up editing by both authors. The authors Markus Janczyk studied psychology at the Universities of Halle-Wittenberg and Reno (USA), earned his doctorate at TU Dortmund University, and completed his habilitation at Julius-Maximilians-Universitt Wrzburg. He is currently a professor at the University of Bremen, where he heads the Research Methods and Cognitive Psychology Group. In his research, he is primarily interested in action control, multitasking, language, applied statistics, and cognitive modeling. Roland Pfister studied psychology at the Julius-Maximilians-University of Wrzburg, where he wrote his doctoral thesis on the cognitive mechanisms of deliberate rule violations. In addition, he works on basic mechanisms of action control, the interplay of perception and action, applied statistics, and the history of psychology. | ||
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed November 3, 2023). | |
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| 650 | 0 | |a Probabilities. | |
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| 650 | 7 | |a Probabilities. |2 fast. | |
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| 880 | 8 | |6 505-00 |a 3.1.2 Sample Statistics and Population Parameters -- 3.2 The Population Parameter -- 3.3 Desired Properties of Parameter Estimators -- 3.4 The Population Parameter v2 -- 4 Hypothesis Testing and Significance -- 4.1 Substantive and Statistical Hypotheses -- 4.1.1 Classification of Statistical Hypotheses -- 4.1.2 Alternative and Null Hypothesis -- 4.2 The Idea of the Significance Test -- 4.2.1 A Fictitious Situation... -- 4.2.2 ... and the Logic of the Significance Test -- 4.2.3 Decisions and Decision Errors -- 5 Difference Hypotheses for Up to Two Means: t-Tests. | |
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