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E-grāmata: Interpreting Statistics for Beginners: A Guide for Behavioural and Social Scientists

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  • Formāts: 204 pages
  • Izdošanas datums: 24-Feb-2022
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781000546187
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Interpreting Statistics for Beginners: A Guide for Behavioural and Social ScientistsPalielināt
  • Formāts: 204 pages
  • Izdošanas datums: 24-Feb-2022
  • Izdevniecība: Routledge
  • Valoda: eng
  • ISBN-13: 9781000546187
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"Interpreting Statistics for Beginners teaches readers to correctly read and interpret results of basic statistical procedures as they are presented in scientific literature, and to understand what they can and cannot infer from such results. The first of its kind, this book explains key elements of scientific paradigms and philosophical concepts that the use of statistics is based on and introduces readers to basic statistical concepts, descriptive statistics, and basic elements and procedures of inferential statistics. Explanations are accompanied with detailed examples from scientific publications to demonstrate how the procedures are used and correctly interpreted. Additionally, Interpreting Statistics for Beginners shows readers how to recognize pseudoscientific claims that use statistics or statements not based on the presented data, an important skill for every professional relying on statistics in their work. Written in an easy-to-read style and focusing on explaining concepts behind statistical calculations, the book is most helpful for readers with no previous training in statistics, and also those wishing to bridge the conceptual gap between doing the statistical calculations and interpreting the results"--

Interpreting Statistics for Beginners teaches readers to correctly read and interpret results of basic statistical procedures as they are presented in scientific literature, and to understand what they can and cannot infer from such results.

Recenzijas

Dr. Iva Sverko, from the "Ivo Pilar" Institute of Social Sciences in Zagreb, Croatia.

'Understanding statistics means being able to make grounded conclusions about the phenomena that surround us, and this book is a means to it. Starting from basic statistical concepts and ending in correlations and difference testing, this book is an excellent primer on essential statistical knowledge. Thanks to its clarity and practical examples included, this book is easy to read and understand, which makes it appealing for various readers. This book approaches main statistical concepts in an accessible and understandable way and is an extremely valuable reading for students, professionals, and researchers. I am sure that a wide audience will find this book as a must have in their regular work.' 'Understanding statistics means being able to make grounded conclusions about the phenomena that surround us, and this book is a means to it. Starting from basic statistical concepts and ending in correlations and difference testing, this book is an excellent primer on essential statistical knowledge. Thanks to its clarity and practical examples included, this book is easy to read and understand, which makes it appealing for various readers. This book approaches main statistical concepts in an accessible and understandable way and is an extremely valuable reading for students, professionals, and researchers. I am sure that a wide audience will find this book as "a must have" in their regular work.' Dr. Iva Sverko, Institute of Social Sciences Ivo Pilar, Zagreb, Croatia

Preface x
Acknowledgements xi
Before we start: General instructions for the exercises xii
1 Scientific paradigms and scientific explanations, pseudoscience 1(23)
1.1 Science, scientific paradigms and statistics
1(8)
1.2 The nature of the causal network of the universe - stochasticism vs. determinism
9(3)
1.3 Scientific explanations
12(3)
1.4 Self-fulfilling prophecies and the corruption of statistical indicators
15(3)
1.5 Science and pseudoscience
18(6)
2 Basic concepts of statistics 24(28)
2.1 Random events
24(1)
2.2 Probability
25(1)
2.3 Entity
26(1)
2.4 Variables and constants
26(1)
2.5 Organization of data, matrix, vector
27(4)
2.6 Population and sample, parameters and statistics
31(3)
2.7 Sampling
34(2)
2.8 Types of samples
36(6)
2.9 Issues about samples to be aware of
42(1)
2.10 Levels of measurement
43(4)
2.11 Continuous and discrete variables
47(1)
2.12 Let us apply what we learned so far!
48(4)
3 Descriptive statistics 52(19)
3.1 Distribution
52(1)
3.2 Percentiles and other quantiles
53(2)
3.3 Measures of central tendency
55(3)
3.4 Measures of variability
58(2)
3.5 How can a distribution be represented?
60(1)
3.6 Let us apply what we learned so far!
60(11)
4 Distributions 71(28)
4.1 Theoretical and empirical distributions
71(1)
4.2 Normal distribution
71(3)
4.3 Poisson distribution
74(1)
4.4 Binomial distribution
75(1)
4.5 Uniform distribution
76(1)
4.6 Deviations from the normal distribution
77(12)
4.7 Standard scores and standardization
89(1)
4.8 Ipsatization
90(3)
4.9 Let us apply what we learned so far!
93(6)
5 Inferential statistics, basic concepts 99(31)
5.1 The central limit theorem
99(4)
5.2 Bootstrapping approach to inferring parameter values
103(1)
5.3 Assessing population parameters, point and interval assessment
104(3)
5.4 The null hypothesis
107(14)
5.5 Bayes' factor and testing statistical hypotheses
121(1)
5.6 Parametric and nonparametric statistics
122(1)
5.7 Let us apply what we learned so far!
123(7)
6 Correlations 130(26)
6.1 Associations between variables
130(1)
6.2 Types of associations between variables
131(5)
6.3 Scattergram
136(1)
6.4 Correlation coefficient
136(5)
6.5 Types of correlation coefficients
141(8)
6.6 Let us apply what we learned so far!
149(7)
7 Statistical tests for comparing two samples 156(23)
7.1 Paired samples and independent samples
156(3)
7.2 Comparing two means - t test
159(2)
7.3 Comparing central tendencies of ordinal data on independent samples - the Mann-Whitney's U test and the Wilcoxon's sum-rank test
161(2)
7.4 Comparing central tendencies of paired samples - the sign test and the Wilcoxon's signed rank test
163(3)
7.5 Comparing standard deviations/variances - Levene's test
166(1)
7.6 Comparing two distributions - Kolmogorov-Smirnov test, chi square and Wald-Wolfowitz test
167(6)
7.7 Let us apply what we learned so far!
173(6)
8 Exercises - let us apply what we learned in this book! 179(9)
Index 188
Prof. Dr. Vladimir Hedrih is a full professor of psychology at the University of Ni in Serbia. He is also the author of the book Adapting Psychological Tests and Measurement Instruments for Cross-Cultural Research: An Introduction.

Dr. Andjelka Hedrih is a research assistant professor at the Mathematical Institute of the Serbian Academy of Sciences and Arts. She is a medical doctor who holds a PhD in Biomedical engineering and technologies. She is the author of a number of published papers on mathematical modelling of biological systems.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
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