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El. knyga: Introducing Research and Data in Psychology: A Guide to Methods and Analysis

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Introducing Research and Data in Psychology shows how research design and data analysis are attainable and useful skills. It introduces both experimental and non-experimental methods of research and the analysis of data using both descriptive and inferential statistics. The uses, interpretation and calculation of common two sample statistical tests are explained. This comprehensive textbook includes the following designed features to help with technique:

  • Practice exam answers to show how to achieve a higher grade
  • Chapter summaries
  • Glossary
  • Case studies and examples
  • Exercises and a full bibliography.
Acknowledgements xiii
Introduction 1(2)
Section One
3(12)
Preliminaries
3(1)
Psychology and common sense explanation
4(2)
Choosing a research question, aims and hypotheses
6(1)
Hypotheses
6(7)
Which hypotheses are you expected to include when writing a report?
7(1)
Points on the wording of hypotheses
8(1)
Some further examples
9(1)
Why do we have all these types of hypotheses?
10(1)
Directional and non-directional hypotheses
10(3)
Independent and dependent variables
13(2)
Section Two
15(32)
Preliminaries
15(1)
The experimental method
16(4)
Laboratory experiments
17(2)
Field experiments
19(1)
Natural experiments and quasi-experiments
20(3)
Natural experiments
20(1)
Quasi-experiments
21(2)
Introduction to non-experimental methods
23(1)
Observation methods
24(9)
Naturalistic observation
27(1)
Participant observation
28(1)
Controlled observations
29(1)
Recording and interpreting data from observational studies
30(3)
Content analysis
33(1)
Case studies
34(2)
Conductive a Case Study
36(1)
Interviews
36(3)
Correlational research
39(3)
Common uses of the correlational method
41(1)
Summary table of methods of investigation
42(1)
Qualitative and quantitative methods
43(4)
Section Three
47(10)
Designs used in research
47(2)
The advantages and disadvantages of different experimental designs
49(3)
Independent groups design
50(1)
Repeated measures design
50(1)
Matched pairs design
51(1)
Single Participant design
52(1)
Design of studies in developmental psychology
52(5)
Longitudinal studies
52(1)
Cross-sectional studies
53(1)
Cohort studies
54(3)
Section Four
57(8)
Sampling
57(8)
Methods of choosing a sample
58(3)
Sample size
61(4)
Section Five
65(8)
The experiment as a social situation
65(4)
Experimenter bias
66(1)
Participant expectations and demand characteristics
67(2)
Reducing bias
69(4)
Section Six
73(6)
Reliability
73(2)
Methods of measuring reliability
73(2)
Validity
75(4)
Internal Validity
75(1)
External Validity
75(1)
Test Validity
76(3)
Section Seven
79(6)
Controlling variables
79(1)
Standardisation of procedures in research
80(1)
Counterbalancing
80(1)
Confounding Variables
81(4)
Constant errors
81(1)
Random errors
82(3)
Section Eight
85(6)
Ethnocentric, cultural and androcentric biases
85(2)
Ethical issues in research
87(4)
The deception dilemma
89(1)
Research on non-human animals
90(1)
Section Nine
91(42)
Presentation of data in reports
92(1)
Tables of scores
92(2)
Graphical representation
94(18)
Line graphs
94(2)
Histograms and bar charts
96(3)
Pie charts
99(1)
General points on drawing graphs
100(2)
Stem and leaf diagrams
102(1)
Box and whisker plots
103(2)
Scattergrams or scattergraphs
105(5)
Correlation coefficients
110(2)
Measures of central tendency
112(4)
The mean
112(1)
The median
113(1)
The mode
114(2)
Distribution curves
116(4)
Normal distributions
116(2)
Skewed distributions
118(2)
Bimodal distributions
120(1)
Measures of dispersion or variability
120(10)
The range
121(1)
The semi-interquartile range
122(1)
Variance
122(1)
Standard deviation (SD)
123(7)
Standard scores and z-scores
130(3)
Section Ten
133(6)
Measurement
133(3)
Data at the nominal level
134(1)
Data at the ordinal level
134(1)
Data at the interval level
135(1)
Data at the ratio level
135(1)
Why is knowledge of levels of measurement important?
136(3)
Section Eleven
139(12)
Tests of statistical inference
139(1)
Different types of Statistical tests
140(5)
When do you use a parametric or non-parametric test?
141(1)
Parametric tests
141(3)
Non-parametric tests
144(1)
Comparison of parametric and non-parametric tests
145(1)
Test selection
145(3)
Tests for a difference between two sets of scores
146(1)
Tests for correlation
147(1)
Summary
148(3)
Section Twelve
151(32)
Tests for data at the nominal level
151(11)
Chi-square test
152(5)
Some controversies over the use of chi-square
157(2)
Sign test
159(3)
Two sample tests for data at the ordinal level
162(7)
Ranking
162(3)
The Mann--Whitney test
165(2)
Wilcoxon signed ranks test
167(2)
Two sample tests for data fulfilling the requirements for the use of parametric tests
169(7)
The t-test for unrelated data
170(3)
The t-test for related data
173(3)
Tests for Correlation
176(7)
Spearman's rank order correlation coefficient
176(3)
Pearson's Product moment correlation coefficient
179(4)
Section Thirteen
183(8)
Interpreting the results of a statistical test
183(4)
At What level of significance can we accept the alternative hypothesis?
185(2)
Type I and Type II errors
187(2)
At what point in the research do you set the level of significance that you will accept?
188(1)
Conclusion
189(2)
Section Fourteen
191(10)
Interpreting qualitative research
191(4)
Reliability and Validity
194(1)
Interpreting observational studies
195(4)
Contents analysis
197(1)
Discourse analysis
198(1)
Interpreting interviews
199(1)
Interpreting case studies
199(1)
Conclusion
200(1)
Section Fifteen
201(6)
Writing reports
201(6)
Title
202(1)
Abstract
202(1)
Introduction
202(1)
Method
203(1)
Results
204(1)
Treatment of results
204(1)
Discussion
204(1)
Conclusion
205(1)
References
205(1)
Appendices
205(2)
Section Sixteen: Study aids
207(8)
Sample exam questions
207(8)
Appendix: Critical value tables 215(18)
Glossary 233(12)
Bibliography 245(4)
Answers to exercises 249(12)
Index 261
Ann Searle is a Principal Moderator for A-level and AS-level coursework.