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Psychology 2810
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# Psych Stats Key Terms2.docx

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Western University

Psychology

Psychology 2810

Riley Hinson

Winter

Description

Correlational research: research to determine whether there is a relationship between two
measures
Scatterplot: a graph in which one of the measures is plotted on the abscissa (x-axis) and the
other is plotted on the ordinate (y-axis), and each participant is located at the point
corresponding to his/her x and y values
The variable being predicted is the y-variable, also known as the criterion variable. The variable
being used to make the prediction is termed the x variable, and is also known as the predictor
variable. (Independent variable is also x, and the dependent variable is y)
Slope: a slant that is an indicator of a relationship between the two variables on a scatterplot
Positive relationship: one variable increases as the other increases
Negative relationship: one variable decreases as the other decreases
Correlation coefficient: used to numerically quantifying the degree of the relationship between
the two variables
Positive correlation / direct relationship: if the two variables both increase together or both
decrease together, with a correlation coefficient between 0.0 and +1.0
Negative correlation or an inverse relationship: if the two variables change in opposite
directions, with a correlation coefficient between 0.0 and -1.0
Linear relationship: what correlation coefficients quantify the strength of
Scaleless: the value of the correlation coefficient is not affected by the units of measurement
If both variables are measured on interval/ratio scales, then the Pearson product-moment
correlation coefficient is used, which is most commonly used in psychological research
Restriction of range problem: I the range of the x or y scores is limited to a small set of values,
this may lead to an underestimation of the degree of correlation between x and y, resulting in
ceiling or floor effects, or using participants that do not display the full range of possible
outcome values
Cases: most often the individual participants of the study, the bivariate data is produced by this
in the calculation of a correlation
Coefficient of determination: simply r squared, and it is used to identify the proportion of
variability in the y scores that is accounted for by the linear relationship between x and y
Regression analysis: predictions about the values of one variable based on information about
values of the other variable if a correlation exists betwee

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