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PSYB01H3 (585)
Chapter 12

Chapter 12 - Detailed & Easy to Learn

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University of Toronto Scarborough
Connie Boudens

Chapter 12 Understanding Research Results: Description and Correlation There are 2 reasons for using statistics: first, statistics are used to describe the data and second, statistics are used to make inferences, on the basis of simply data, about a population SCALES OF MEASUREMENT: A REVIEW The levels of the variable can be described using 1 of 4 scales of measurement: nominal, ordinal, interval and ratio The levels of nominal scale variables have no numerical, quantitative properties. The levels are simply different categories or groups. Most independent variable in experiments are nominal Variables with ordinal scale levels involve minimal quantitative distinctions. We can rank order the levels of the variable being studies from lowest to highest Interval and ratio scale variables have much more detailed quantitative properties. With an interval scale variable, the intervals between the levels are equal in size. There is no absolute zero point that indicated an absence of mood Ratio scale variables have both equal intervals and an absolute zero point that indicates the absence of the variable being measured. Time, weight, length etc are the best examples ANALYZING THE RESULTS OF RESEARCH INVESTIGATIONS Depending on the way that the variables are studies, there are 3 basic ways of describing the results: (1) comparing group percentages, (2) correlating scores of individuals on two variables and (3) comparing group means Comparing group percentages Correlating individual scores o Needed when you do not have distinct groups of subjects o Instead, individuals are measure on 2 variables, and each variable has a range of numerical values Comparing group means o Much research is design to compare the mean responses of participants in two or more groups FREQUENCY DISTRIBUTIONS www.notesolution.com
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