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Making Sense of Data and Statistics in Psychology - Brian Greer

Making Sense of Data and Statistics in Psychology

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Published: 12th December 2001
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Making Sense of Data and Statistics in Psychology confronts the pedagogic challenge of teaching statistics to students in psychology and related disciplines. Recognising the heterogeneous nature of students' mathematical backgrounds and motivations, the authors adopt an innovative approach while ensuring ready integration into orthodox undergraduate statistics courses at introductory and post-introductory levels. Before being introduced to formal statistics, students are encouraged to develop a 'feel' for data, particularly through visual representation. Making extensive use of exploratory data analysis (EDA), the text emphasises conceptual rather than technical or procedural understanding.

'The book reads very well... Pleasantly relaxed and informal. It is well structured and full of interesting, instructional and germane verbal examples and pictorial illustrations.' - Neil Frude, Cardiff University 'Coverage is excellent... The authors obviously have a great deal of experience in teaching, and have brought this to bear... I like the way the authors describe the procedure of carrying out statistical tests. It doesn't befuddle students with mathematics.' - Jeremy Miles, York University 'The authors' style is designed to communicate very directly with the reader, and, I think, achieves this objective well.' - Lynne Duncan, University of Dundee

Prefacep. x
Acknowledgementsp. xiii
Statistics in psychologyp. 1
What does this book offer?p. 1
OK, so why statistics?p. 4
Variability in psychologyp. 6
Is psychology a science?p. 9
Chapter reviewp. 13
Making Sense of Basic Designsp. 15
Variablesp. 17
Ways of measuring people (and other animals)p. 17
Nature of data generatedp. 19
The idea of a variablep. 22
Variables under experimental controlp. 25
Investigating relationships between variablesp. 27
Chapter reviewp. 28
Describing and summarising datap. 29
Summary statisticsp. 29
Graphical representations of distributionsp. 38
Chapter reviewp. 43
Seeing patterns in data: Comparingp. 44
Comparing proportionsp. 44
Comparison between independent samplesp. 50
Comparison within paired datap. 54
On not jumping to conclusionsp. 57
Comparisons as relationships between variablesp. 58
Chapter reviewp. 59
Seeing patterns in data: Correlatingp. 60
The concept of correlationp. 60
Correlation and causationp. 67
On not jumping to conclusionsp. 68
Chapter reviewp. 70
The relevance of probabilityp. 71
Measuring probabilityp. 71
Counting headsp. 78
The role of the normal distributionp. 81
Predicting an election: A sampling examplep. 83
A key idea: Conditional probabilityp. 85
Inference from sample to population: An examplep. 88
Chapter reviewp. 93
Statistical tests: Comparingp. 94
Comparing proportionsp. 94
Comparison between independent groupsp. 100
Comparison within paired datap. 114
Another case of paired data: Matched pairs designsp. 119
Chapter reviewp. 120
Statistical tests: Correlatingp. 121
Quantifying strength of relationshipp. 121
A rank-based alternativep. 126
Testing for significancep. 131
Correlation and causationp. 134
Example: Burt's data on juvenile delinquencyp. 136
Fitting a straight linep. 139
An example of regression lines: Analysis of Burt datap. 142
Testing for significance of regressionp. 145
Chapter reviewp. 145
Experimentation in psychologyp. 146
Putting a little more meat on the bonesp. 146
Recap: The empirical processp. 146
Experimental designsp. 147
Pros and cons of the various designsp. 152
Coping with transferp. 153
Summing up: Design, validity and insidious variablesp. 158
Statistical inferencep. 158
Choosing the right statistical testp. 167
Chapter reviewp. 172
Making Sense of Bigger Designsp. 173
Seeing patterns in data: Comparing more than two groupsp. 175
Examples of comparisonsp. 175
Chapter reviewp. 186
Statistical tests: Comparing more than two groupsp. 187
Extending from two to more than two groupsp. 187
Independent groupsp. 188
Repeated measuresp. 194
ANOVA terminologyp. 197
ANOVA logic: A summaryp. 197
Rank-based alternativesp. 198
Settling differences: Post-hoc testsp. 201
Chapter reviewp. 205
Seeing patterns in data: Comparisons involving more than one independent variablep. 206
Illustrative examplesp. 206
Beyond graphical analysisp. 217
Chapter reviewp. 218
Statistical tests: Comparing more than one independent variablep. 219
For example ...p. 219
Settling more differencesp. 226
Chapter reviewp. 232
Relating: Multiple variablesp. 233
Introducing multiple regression analysisp. 233
Variations on the multiple regression analysis themep. 242
The relative strengths and weaknesses of MRA and ANOVAp. 257
Chapter reviewp. 258
Overviewp. 259
On seeing the wood for the trees: What are the big ideas?p. 259
Book reviewp. 267
Indexp. 269
Table of Contents provided by Syndetics. All Rights Reserved.

ISBN: 9780333629697
ISBN-10: 0333629698
Audience: General
Format: Paperback
Language: English
Number Of Pages: 272
Published: 12th December 2001
Publisher: SPRINGER VERLAG GMBH
Country of Publication: GB
Dimensions (cm): 24.61 x 18.9  x 1.52
Weight (kg): 0.52
Edition Number: 1