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Slide 1 ___________________________________ ___________________________________ Understanding Research Results ___________________________________ Chapter 12 ___________________________________ ___________________________________ ___________________________________ ___________________________________ Slide 2 ___________________________________ Why do we use statistics • Statistics are used to describe the data ___________________________________ • When comparing groups in our experiment, we look for statistically significant differences between our ___________________________________ conditions. This tells us whether or not our experimental condition has an effect. • Statistics are analyzed, and statistical significance takes into account the number ___________________________________ of subjects when analyzing for differences. ___________________________________ ___________________________________ ___________________________________ Slide 3 ___________________________________ Review of Scales and Measurement • Nominal Scale Variables ___________________________________ – Have no numerical or quantitative properties – The levels are simply different categories or groups ___________________________________ – Many independent variables in experiments are nominal (e.g. gender, marital status, hand dominance)  code or assign a number to the group (male=1, female=2) ___________________________________ ___________________________________ ___________________________________ ___________________________________

Slide 4 ___________________________________ Ordinal Scale Variables – These variables involve minimal quantitative ___________________________________ distinctions  can rank order levels of the variable from lowest to highest. – Rank the stressors in your life from lowest to hightest. •  Exams •  Grades ___________________________________ •  Significant other •  Parental approval •  Scholarship – All we know is the order, the strength of the stressor ___________________________________ is not known. ___________________________________ ___________________________________ ___________________________________ Slide 5 ___________________________________ Interval and Ratio Scale Variables – With interval scale variables, the intervals between the levels ___________________________________ are equal in size – There is no zero point indicating the absence of something  as in there is no absence of mood. – Ratio scale variables have both equal intervals and a absolute zero point that indicates the absence of the variable ___________________________________ being measured  time, weight, length and other physical measures are the best examples of ratio scales. – Interval and ratio data are conceptually different but the statistical procedures used to analyze the data are exactly the same. – With both interval and ratio scales the data can be ___________________________________ summarized using the mean…eg. The average mood of the group was 6.5. ___________________________________ ___________________________________ ___________________________________ Slide 6 ___________________________________ Analyzing the Results of Research Investigations • Comparing group percentages ___________________________________ • Correlating scores of individuals on two variables ___________________________________ • Comparing group means ___________________________________ ___________________________________ ___________________________________ ___________________________________

Slide 7 ___________________________________ Comparing Group Percentages • Type of analysis you can run when you have two ___________________________________ distinct groups or populations you are comparing and the variable is nominal as in whether or not males vs. females helped or not (nominal-yes vs. no). • If you analyzed whether males and females differ in ___________________________________ the way they helped you would count the number of times females helped, and then the number of times males helped and get a percentage of each. • Next we would run statistical analysis on the ___________________________________ differences between the percentages to see if the groups were significantly different. ___________________________________ ___________________________________ ___________________________________ Slide 8 ___________________________________ Interpreting Statistical Analysis • For example: In the current study if there were 30 females and ___________________________________ 30 males in each condition, and 24 females helped, as opposed to 21 males, • We would be able to say that 80% of the females elected to help as compared to 70% of the males. Next we would run statistical analysis on 80% vs. 70% using a simple t-test. ___________________________________ • The t-test takes into consideration the number of participants in the group. Therefore with a t (58)=1.56. • In order for the difference to be significant with 50 subjects, the t score, with 60 participants would have to be at least a 2.0, (according to the tables at the back of the book (p361) • Therefore, there was no significant difference between males ___________________________________ and females in a helping situation. ___________________________________ ___________________________________ ___________________________________ Slide 9 ___________________________________ Correlating Individual Scores • Used when you don’t have distinct groups of ___________________________________ subjects. • Instead, individual subjects are measured on two variables, and each variable has a range of numerical values  correlation between ___________________________________ personality types and profession. • Two variables per subject  with the variables given different numerical values. (could be ___________________________________ something that already has numerical values  test performance and blood pressure) • Does NOT imply causation, only a relationship. ___________________________________ ___________________________________ ___________________________________

Slide 10 ___________________________________ Comparing Group Means • Compare the mean of one group to that of a ___________________________________ second group to determine if there are any differences between the two groups. • Again, statistical analysis is performed, based on ___________________________________ the number of groups, and the number of participants to determine if the difference is statistically significant and therefore conclusions can be made about treatment and control ___________________________________ groups and whether or not the hypothesis was supported. ___________________________________ ___________________________________ ___________________________________ Slide 11 ___________________________________ Which Statistics to use • T-statitistic -statitistical measure for assessing ___________________________________ whether or not there is a difference between two groups. • Formuala: ___________________________________ • t = group difference within group difference ___________________________________ ___________________________________ ___________________________________ ___________________________________ Slide 12 ___________________________________ F-statistic (ANOVA) • Statistical measure for assessing whether or ___________________________________ not two or more groups are equal. • Cannot use a t-test with more than two groups. • Also used to analyze an interaction. ___________________________________ • It is a ratio of two types of variance • Formula F= systematic variance (variability b/w groups) ___________________________________ Error Variance (variability within groups) ___________________________________ ___________________________________ ___________________________________