Summary
Contents
Subject index
Understanding and Using Statistics in Psychology takes the fear out of psychological statistics to help students understand why statistics are carried out, how to choose the best test, how to carry out the tests, and then perform the analysis in SPSS. Emphasizing the place of statistical analysis in the process of conducting research, from design to report writing, this accessible and straightforward guide takes a non-technical approach, encouraging the reader to understand why a particular test is being used and what the results mean in the context of a psychological study. The focus is on meaning and understanding rather than numerical calculation.
Relationships between Variables: Correlation and Regression
Relationships between Variables: Correlation and Regression
What's in This Chapter?
- Association
- Correlation
- Regression
- Interpreting correlation and regression
- Calculating correlation coefficients: Pearson and Spearman
- Causality
- Using SPSS
Key Terms
association
causal relationship
confidence interval
correlation coefficient
covariance
descriptive statistic
dicohotomania
equation for a straight line
eugenics
experiment
Fisher's z transformation
inferential statistic
Kendall's tau-a
line of best fit
non-parametric correlation
normal distribution
Pearson correlation coefficient
post hoc justification
power
proportion of variance
regression line
residual
sample statistics
scatterplot
Simpson's paradox
Spearman correlation
standard deviation
standardised slope
statistical significance
y-intercept
Introduction
So far in this book we have considered ways of comparing groups of individuals. In particular, we have looked at differences between groups. All our hypotheses so far have been along the lines of whether one set of scores is bigger, wider, more frequent etc. than another set of scores. Not all data are like that and sometimes we don't want to know about difference, we want to know about ...
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