Basic statistics for psychologists / Marc Brysbaert.

Contributor(s):

Brysbaert, Marc

Material type: Text

TextPublication details: New York : Palgrave Macmillan, 2011.Description: 413 p. 25 cmISBN:

9780230275423 (pbk.)
0230275427 (pbk.)

Subject(s):

DDC classification:

150.15195 BRY

Contents:

Machine generated contents note:. Preface -- Using statistics in psychology research -- Summarising data using the frequency distribution -- Summarising data using measures of central tendency -- Summarising data using measures of variability -- Standardised scores, normal distribution and probability -- Using the t-test to measure the difference between independent groups -- Interpreting the results of a statistical test -- Using non-parametric tests to measure the difference between independent groups -- Using the t-test to measure change in related samples -- Using non-parametric tests to measure change in related samples -- Improving predictions through the Pearson correlation coefficient -- Improving predictions through non-parametric tests: The Spearman rank correlation and the chi-square test for independence -- Using analysis of variance (ANOVA) to compare more than two conditions -- Post-hoc tests in ANOVA and multiple regression analysis.

Summary: Basic Statistics for Psychologists combines clear explanations of statistical concepts and tests with a guide to using SPSS, providing an invaluable resource for psychology students. Highly readable and with innovative learning features throughout, this book offers a comprehensive introduction to statistics and their use in social science--.

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Standard Loan	Moylish Library Main Collection	150.15195 BRY (Browse shelf(Opens below))	1	Available		39002100478461

Enhanced descriptions from Syndetics:

The emphasis upon methods of statistical research in psychology is often overlooked by beginning undergraduate students and subsequently, many find difficulty in approaching this unexpected yet so often integral topic of any given psychology degree. Subsequently this clearly written and comprehensive textbook offers itself as a guide to those students looking for a clear introduction on how to use statistics in psychological research. Crucially, students will be equipped with the key methods of statistical inference and learn how to interpret the results of various statistical tests. Expect to learn how to summarise data using the frequency distribution, measures of central tendency, variability as well how to employ the t-test and non-parametric tests for various types of groups and samples.

This core adoptable textbook covers all areas of undergraduate statistics, with good formulas and explanations for calculations and will aid students with the knowledge and tools necessary to developing their ability to conduct reliable and methodical research using statistics. This is an incredibly helpful and informative read for undergraduate students taking research methods and statistics courses in psychology.

Includes index.

Basic Statistics for Psychologists combines clear explanations of statistical concepts and tests with a guide to using SPSS, providing an invaluable resource for psychology students. Highly readable and with innovative learning features throughout, this book offers a comprehensive introduction to statistics and their use in social science--.

Table of contents provided by Syndetics

Preface (p. viii)
Tour of book (p. xii)
Symbols and abbreviations (p. xiv)
Chapter l Using statistics in psychology research (p. 1)
1.1 The need for reliable and valid empirical studies (p. 2)
1.2 The population and the sample (p. 3)
1.3 Different types of research in psychology (p. 5)
1.4 Which statistics should we calculate? (p. 15)
1.5 Answers to chapter questions (p. 21)
Chapter 2 Summarising data using the frequency distribution (p. 25)
2.1 Introduction (p. 26)
2.2 Frequency distribution tables (p. 27)
2.3 Frequency distribution graphs (p. 33)
2.4 The shape of a frequency distribution (p. 39)
2.5 Making a frequency distribution table and a frequency distribution graph in SPSS (p. 43)
2.6 Going further: continuous variables, real limits and theoretical distributions (p. 55)
2.7 Answers to chapter questions (p. 56)
2.8 Learning check solutions (p. 57)
Chapter 3 Summarising data using measures of central tendency (p. 56)
3.1 The need for summary data and the danger of them (p. 60)
3.2 The mean (p. 61)
3.3 The median (p. 64)
3.4 The mode (p. 66)
3.5 Which measure of central tendency to use? (p. 67)
3.6 Comparing the different measures of central tendency (p. 70)
3.7 Calculating measures of central tendency in SPSS (p. 70)
3.8 Going further: using interpolation to find a more exact value of the median (p. 72)
3.9 Answers to chapter questions (p. 74)
3.10 Learning check solutions (p. 75)
Chapter 4 Summarising data using measures of variability (p. 76)
4.1 The underestimated importance of variability (p. 77)
4.2 The range (p. 78)
4.3 Standard deviation and variance (p. 79)
4.4 Calculating the range and standard deviation with SPSS (p. 87)
4.5 Going further a computational formula for the standard deviation (p. 88)
4.6 Answers to chapter questions (p. 90)
4.7 Learning check solutions (p. 91)
Chapter 5 Standardised scores, normal distribution and probability (p. 92)
5.1 The need for standardised scores (p. 93)
5.2 Transforming raw scores into z-scores (p. 93)
5.3 Interpreting z-scores (p. 94)
5.4 Transforming z-scores into raw scores (p. 95)
5.5 The normal distribution (p. 96)
5.6 Probability (p. 103)
5.7 Z-scores, normal distributions, probabilities and percentiles (p. 107)
5.8 Calculating z-scores and probabilities in SPSS (p. 115)
5.9 Going further defining the shape of the normal distribution (p. 119)
5.10 Answers to chapter questions (p. 119)
5.11 Learning check solutions (p. 121)
Chapter 6 Using the t-test to measure the difference between independent groups (p. 122)
6.1 Few differences between groups can be spotted with the naked eye (p. 123)
6.2 The standard error of the mean (p. 128)
6.3 The t-statistic for independent samples (p. 137)
6.4 Hypothesis testing on the basis of the t-statistic (p. 141)
6.5 Calculating a t-test for independent samples with SPSS (p. 152)
6.6 Going further: unequal sample sizes and unequal variances (p. 156)
6.7 Answers to chapter questions (p. 158)
6.8 Learning check solutions (p. 161)
Chapter 7 Interpreting the results of a statistical test (p. 162)
7.1 Confidence intervals and their relation to statistical tests (p. 164)
7.2 More on the interpretation of significant effects (p. 170)
7.3 The effect size (p. 177)
7.4 How to interpret non-significant effects (p. 183)
7.5 How many participants should I include in my experiment? (p. 184)
7.6 Adding confidence intervals to your graphs in SPSS (p. 188)
7.7 Going further: one- and two-tailed tests, and a mathematical summary (p. 192)
7.8 Answers to chapter questions (p. 194)
7.9 Learning check solutions (p. 197)
Chapter 8 Non-parametric tests of difference between independent groups (p. 199)
8.1 The Mann-Whitney U-test for ordinal data (p. 200)
8.2 The one-way chi-square test for nominal data (p. 217)
8.3 Answers to chapter questions (p. 219)
8.4 Learning check solutions (p. 221)
Chapter 9 Using the t-test to measure change in related samples (p. 223)
9.1 The t-statistic for repeated measures (p. 224)
9.2 The effect size, likelihood ratio and power of a t-test with repeated measures (p. 228)
9.3 The confidence interval for a design with repeated measures (p. 232)
9.4 Step by step: a t-test for repeated measures (p. 235)
9.5 Running a t-test with repeated measures in SPSS (p. 239)
9.6 Going further: the relationship between SD D , SD 1 and SD 2 (p. 240)
9.7 Answers to chapter questions (p. 241)
9.8 Learning check solutions (p. 242)
Chapter 10 Non-parametric tests to measure changes in related samples (p. 243)
10.1 The Wilcoxon signed-rank statistic (p. 244)
10.2 The Wilcoxon signed-rank test (p. 248)
10.3 How to report a Wilcoxon signed-rank test (p. 249)
10.4 Adding a confidence interval to your graph (p. 249)
10.5 The Wilcoxon signed-rank test as an alternative to the t-test for related samples (p. 252)
10.6 Step by step: the Wilcoxon signed-rank test (p. 254)
10.7 The Wilcoxon signed-rank test in SPSS (p. 256)
10.8 Answers to chapter questions (p. 259)
Chapter 11 Improving predictions through the Pearson correlation coefficient (p. 261)
11.1 The Pearson product-moment correlation coefficient (p. 262)
11.2 Significance of the Pearson product-moment correlation coefficient (p. 280)
11.3 Calculating the Pearson product-moment correlation in SPSS (p. 286)
11.4 Going further: using the t-distribution to calculate the p-value of a Pearson correlation and using Pearson's correlation as an effect size (p. 292)
11.5 Answers to chapter questions (p. 295)
Chapter 12 Improving predictions through non-parametric tests (p. 298)
12.1 The Spearman rank correlation for ordinal data and interval/ratio data (p. 299)
12.2 The chi-square test of independence for nominal data (p. 307)
12.3 Answers to chapter questions (p. 317)
Chapter 13 Using analysis of variance for multiple independent variables (p. 319)
13.1 Using analysis of variance to compare groups of people (p. 320)
13.2 Using analysis of variance to compare conditions within people (p. 334)
13.3 Analysis of variance with one between-groups variable and one repeated measure (p. 343)
13.4 Answers to chapter questions (p. 355)
Chapter 14 Going further: more than two levels and multiple predictors (p. 357)
14.1 Analysing a study with three groups of participants (p. 358)
14.2 Analysing a repeated measures study with more than two levels (p. 371)
14.3 Working with more than one predictor in a regression analysis (p. 381)
14.4 Answers to chapter questions (p. 390)
References (p. 391)
Appendices (p. 393)
Index (p. 407)

Author notes provided by Syndetics

MARC BRYSBAERT is currently Research Professor of Psychology at Ghent University, Belgium. Previously he was Professor of Psychology at Royal Holloway, University of London, where he taught both statistics and research methods and developed this textbook.

Marc has extensive publishing experience and has written the market-leading book on 'Conceptual and Historical Issues in Psychology', published by Pearson, as well as a Dutch Handbook of Psychology, and more.