Research methods and statistics in psychology/
Coolican, Hugh
Research methods and statistics in psychology/ Hugh Coolican - London: Psychology, 2014. - 773 p.
Psychology, science and research
Why psychology and science?: Science - not a subject but a way of thinking; So what is
this scientific method then? Asking why? Generating theories for laws; The counterproductive
method testing testing scientific theories How psychologists actually do scientific research
What are the main features of a psychological investigation? Qualitative data and
qualitative approaches
Measuring people — variables, samples and the qualitative critique
Variables; Psychological constixicts; Operational definitions of psychological constmcts;
Reliability and validity; Samples; Probability- and non-probability-based sampling methods;
Sample size; Introducing the quantitative/qualitative debate; Relative values of quantitative
and qualitative studies
Experiments and experimental designs in psychology
The role of experiments in gathering evidence - demonstrating cause and effect;
Alternative explanations; IVs, DVs and features of the true experiment; Simple
experimental designs; Participant variables and non-equivalent groups; Repeated measures
design, Matched-pairs design; Single participant and small n design
Validity in psychological research
The interpretation of causes in experiments; Sources of variance in the experiment;
Validity in experiments and other research designs; Types of validity (Statistical conclusion
validity. Internal validity, Construct validity); Tackling confounds in psychological research;
Expectancy; Extemal validity; Meta-analysis
Quasi-experiments and non-experiments
The field and the laboratory; True experiments and field experiments; The quasi-
experiment; Non-experimental research; Control and validity in the laboratoi7 and in the
feld (advantages and disadvantages of the laboratory); Studies in the field
Observational methods - watching and being with people
Obseo/ation in general; Obsei^ation as a technique or as an overall design; Structured
obseir/ation; Controlled observation; Naturalistic obsevation; Qualitative non-particip mt
observation; Role-play and simulation; The diary method; Participant obsevation; Ca e
studies; Indirect observation
7 Interview methods - asking people direct questions
Self-report methods: Structured interviews; Effects of interpersonal vanables in inteiviews:
Types of inten/iew; Semi-structured or open inteiviewing gathering qualitative data:
Recording the interview; Surveys
8 Psychological tests and measurement scales
Measurement vs. information gathering - scales, tests, inventories and questionnair-es;
Open and closed questions: Attitude scales: Central issues in the use of psychological
scales: Scale items - what to avoid in statement construction; Pr-ojective tests; Intelligence
and personality tests: Reliability, validity and standar-disation
9 Comparison studies - cross-sectional, longitudinal and cross-cultural studies
What are comparison studies? Cross-sectional studies: Longitudinal studies: Evaluation
of longitudinal and cross-sectional studies: Cross-cultural studies: Ethnocentrism;
The emic-etic distinction
10 Qualitative approaches in psychology
Psychology and the positivist paradigm: The problem with quantification in psychological
research: Qualitative data gathering: Types of qualitative method: Thematic analysis:
Grounded theory: Interpretive Phenomenological Analysis, Discourse analysis: Action
research: Participative and collaborative research: Memories as narratives: Reflexivity:
Contemporary qualitative methods
I I Ethical issues in psychological research
Publication and access to data: The conduct of research with human participants:
Deception: Debriefing: Stress and discomfort: Right to withdraw; Investigator power
Involuntary participation: Intervention: Research with animals - case for and against;
Conclusions
PART 2 Analysing data and writing reports
12 Analysing qualitative data
Quantitative analysis of qualitative data - content analysis: Qualitative analysis of qualitative
data: Doing qualitative research: Considerations for a qualitative project: The data-gathering
process: Data analysis; Procedures in major approaches: Quality in qualitative research -
what of reliability and validity? The emergence of guidelines; Useful websites
13 Statistics - organising the data
Measuring things; Different levels of measurement; Summarising data; Measures of central
tendency (mean, median, mode): Measures of dispersion (range, interquartile and semi-
interquartile range, mean deviation, standard deviation and variance): Population
parameters, sample statistics and sampling error Using SPSS to calculate statistics:
Appendix - statistical notation and symbols
14 Graphical representation of data
Graphs in general; The bar chart: Line charts; The histogram; Exploratory data analysis;
Stem and leaf display; Box-plots; Using SPSS to produce your charts
15 Frequencies and distributions
Dealing with larger data sets; Percentiles, deciles and quartiles; The noimal distribution;
z scores/Standard scores; Standardisation of psychological measurements; Sampling
distributions; Confidence inten/als; Skewed distributions; Kurtosis in distributions
16 Significance testing — was it a real effect?
Significance decisions; The null and alternative hypotheses; Probability; Rejecting the null
hypothesis; The standard level of significance - 5% significance level; Cntical values;
Significance testing -- the basic model; Rejection regions; Frequency distributions and
probability distributions; Type I eiroi's; Type II eirors; The question of power and effect
size; Significance levels; Directional and non-directional hypotheses - one- and two-tailed
tests; Conducting a significance test
17 Testing for differences between two samples
Tests of difference between two conditions or groups (Parametric tests); Data assumptions
for parametric tests; Non-parametric tests of difference; Wilcoxon's T; Mann-Whitney U:
The binomial sign test; SPSS procedures for two condition difference tests; Effect size and
power
18 Tests for categorical variables and frequency tables
Tests on two-way frequency tables; Unrelated data - the chi-square test of association;
The 2x2 chi-square; More complex chi-square data (r x c designs); The 'goodness of fit'
test for a single variable; SPSS procedure for conducting an r x c chi-square test; Multi-way
frequency tables and log-linear analysis; Condurting a three-way frequency analysis
in SPSS
19 Correlation and regression
Simple correlation; Measurement of coirelation; Correlation coefficients - Peai^on's
product-moment, Spearman s rho; Significance and correlation coefficients; SPSS procedures
for correlation, What you can t assume with a correlation; Categorical variables; Common
uses of con elation in psychology; Regression and multiple regression; Multiple predictions;
Partial and semi-partial coi relation. Regression coefficients; Effect size and power
Conducting a regression analysis in SPSS
20 Multi-level analysis - differences between more than two conditions (ANOVA)
More complex tests; One-way ANOVA - unrelated designs; The F ratio statistic; A priori
and post hoc comparisons; Estimating power in one-way ANOVA; Non-parametric
ANOVA equivalent Kruskal -Wallis; Multivanate Analysis of Variance (MANOVA);
ANCOVA - Analysis of Co-variance; SPSS procedures for one-way ANOVA
21 Multi-factorial ANOVA designs
Using two or more independent vanables: Central features of multi-factonal designs: Effect
sizes and power Three-way ANOVA calculation; SPSS procedure for two-way between
groups ANOVA
22 ANOVA for repeated measures designs
Related designs: Between subjects and between conditions variation: Two-way (related)
design: ANOVA mixed design - one repeated measure and one unrelated factor More
complex ANOVA designs: Effect size and power A non-parametnc equivalent the
Fredman test for comelated samples: SPSS procedures for repeated measures ANOVA
23 Choosing a significance test for your data (and internet resources)
Choosing an appropnate test: Tests for two samples: Tests for more than two samples:
To calculate or not to calculate? Internet resources
24 Planning your practical and writing up your report
Planning your practical project overall aim, design, samples, materials, procedure, ethics:
Writing your practical report: Sections of a standard report; Quantitative and qualitative
report features: Comments on a student practical report: A better version of the report
9781444170115
150.727 / COO/R
Research methods and statistics in psychology/ Hugh Coolican - London: Psychology, 2014. - 773 p.
Psychology, science and research
Why psychology and science?: Science - not a subject but a way of thinking; So what is
this scientific method then? Asking why? Generating theories for laws; The counterproductive
method testing testing scientific theories How psychologists actually do scientific research
What are the main features of a psychological investigation? Qualitative data and
qualitative approaches
Measuring people — variables, samples and the qualitative critique
Variables; Psychological constixicts; Operational definitions of psychological constmcts;
Reliability and validity; Samples; Probability- and non-probability-based sampling methods;
Sample size; Introducing the quantitative/qualitative debate; Relative values of quantitative
and qualitative studies
Experiments and experimental designs in psychology
The role of experiments in gathering evidence - demonstrating cause and effect;
Alternative explanations; IVs, DVs and features of the true experiment; Simple
experimental designs; Participant variables and non-equivalent groups; Repeated measures
design, Matched-pairs design; Single participant and small n design
Validity in psychological research
The interpretation of causes in experiments; Sources of variance in the experiment;
Validity in experiments and other research designs; Types of validity (Statistical conclusion
validity. Internal validity, Construct validity); Tackling confounds in psychological research;
Expectancy; Extemal validity; Meta-analysis
Quasi-experiments and non-experiments
The field and the laboratory; True experiments and field experiments; The quasi-
experiment; Non-experimental research; Control and validity in the laboratoi7 and in the
feld (advantages and disadvantages of the laboratory); Studies in the field
Observational methods - watching and being with people
Obseo/ation in general; Obsei^ation as a technique or as an overall design; Structured
obseir/ation; Controlled observation; Naturalistic obsevation; Qualitative non-particip mt
observation; Role-play and simulation; The diary method; Participant obsevation; Ca e
studies; Indirect observation
7 Interview methods - asking people direct questions
Self-report methods: Structured interviews; Effects of interpersonal vanables in inteiviews:
Types of inten/iew; Semi-structured or open inteiviewing gathering qualitative data:
Recording the interview; Surveys
8 Psychological tests and measurement scales
Measurement vs. information gathering - scales, tests, inventories and questionnair-es;
Open and closed questions: Attitude scales: Central issues in the use of psychological
scales: Scale items - what to avoid in statement construction; Pr-ojective tests; Intelligence
and personality tests: Reliability, validity and standar-disation
9 Comparison studies - cross-sectional, longitudinal and cross-cultural studies
What are comparison studies? Cross-sectional studies: Longitudinal studies: Evaluation
of longitudinal and cross-sectional studies: Cross-cultural studies: Ethnocentrism;
The emic-etic distinction
10 Qualitative approaches in psychology
Psychology and the positivist paradigm: The problem with quantification in psychological
research: Qualitative data gathering: Types of qualitative method: Thematic analysis:
Grounded theory: Interpretive Phenomenological Analysis, Discourse analysis: Action
research: Participative and collaborative research: Memories as narratives: Reflexivity:
Contemporary qualitative methods
I I Ethical issues in psychological research
Publication and access to data: The conduct of research with human participants:
Deception: Debriefing: Stress and discomfort: Right to withdraw; Investigator power
Involuntary participation: Intervention: Research with animals - case for and against;
Conclusions
PART 2 Analysing data and writing reports
12 Analysing qualitative data
Quantitative analysis of qualitative data - content analysis: Qualitative analysis of qualitative
data: Doing qualitative research: Considerations for a qualitative project: The data-gathering
process: Data analysis; Procedures in major approaches: Quality in qualitative research -
what of reliability and validity? The emergence of guidelines; Useful websites
13 Statistics - organising the data
Measuring things; Different levels of measurement; Summarising data; Measures of central
tendency (mean, median, mode): Measures of dispersion (range, interquartile and semi-
interquartile range, mean deviation, standard deviation and variance): Population
parameters, sample statistics and sampling error Using SPSS to calculate statistics:
Appendix - statistical notation and symbols
14 Graphical representation of data
Graphs in general; The bar chart: Line charts; The histogram; Exploratory data analysis;
Stem and leaf display; Box-plots; Using SPSS to produce your charts
15 Frequencies and distributions
Dealing with larger data sets; Percentiles, deciles and quartiles; The noimal distribution;
z scores/Standard scores; Standardisation of psychological measurements; Sampling
distributions; Confidence inten/als; Skewed distributions; Kurtosis in distributions
16 Significance testing — was it a real effect?
Significance decisions; The null and alternative hypotheses; Probability; Rejecting the null
hypothesis; The standard level of significance - 5% significance level; Cntical values;
Significance testing -- the basic model; Rejection regions; Frequency distributions and
probability distributions; Type I eiroi's; Type II eirors; The question of power and effect
size; Significance levels; Directional and non-directional hypotheses - one- and two-tailed
tests; Conducting a significance test
17 Testing for differences between two samples
Tests of difference between two conditions or groups (Parametric tests); Data assumptions
for parametric tests; Non-parametric tests of difference; Wilcoxon's T; Mann-Whitney U:
The binomial sign test; SPSS procedures for two condition difference tests; Effect size and
power
18 Tests for categorical variables and frequency tables
Tests on two-way frequency tables; Unrelated data - the chi-square test of association;
The 2x2 chi-square; More complex chi-square data (r x c designs); The 'goodness of fit'
test for a single variable; SPSS procedure for conducting an r x c chi-square test; Multi-way
frequency tables and log-linear analysis; Condurting a three-way frequency analysis
in SPSS
19 Correlation and regression
Simple correlation; Measurement of coirelation; Correlation coefficients - Peai^on's
product-moment, Spearman s rho; Significance and correlation coefficients; SPSS procedures
for correlation, What you can t assume with a correlation; Categorical variables; Common
uses of con elation in psychology; Regression and multiple regression; Multiple predictions;
Partial and semi-partial coi relation. Regression coefficients; Effect size and power
Conducting a regression analysis in SPSS
20 Multi-level analysis - differences between more than two conditions (ANOVA)
More complex tests; One-way ANOVA - unrelated designs; The F ratio statistic; A priori
and post hoc comparisons; Estimating power in one-way ANOVA; Non-parametric
ANOVA equivalent Kruskal -Wallis; Multivanate Analysis of Variance (MANOVA);
ANCOVA - Analysis of Co-variance; SPSS procedures for one-way ANOVA
21 Multi-factorial ANOVA designs
Using two or more independent vanables: Central features of multi-factonal designs: Effect
sizes and power Three-way ANOVA calculation; SPSS procedure for two-way between
groups ANOVA
22 ANOVA for repeated measures designs
Related designs: Between subjects and between conditions variation: Two-way (related)
design: ANOVA mixed design - one repeated measure and one unrelated factor More
complex ANOVA designs: Effect size and power A non-parametnc equivalent the
Fredman test for comelated samples: SPSS procedures for repeated measures ANOVA
23 Choosing a significance test for your data (and internet resources)
Choosing an appropnate test: Tests for two samples: Tests for more than two samples:
To calculate or not to calculate? Internet resources
24 Planning your practical and writing up your report
Planning your practical project overall aim, design, samples, materials, procedure, ethics:
Writing your practical report: Sections of a standard report; Quantitative and qualitative
report features: Comments on a student practical report: A better version of the report
9781444170115
150.727 / COO/R