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PSY 121

Chapter 12 and Chapter 13

TermDefinition
effect size general term that refers to the strength of association between variables; a type of correlation (pearson r is one indicator) general guide: 0.15 = small effects, 0.30 = medium effects, 0.40 or above = large effects
standard deviation (SD) average deviation of scores from the mean. SD = small; scores are close to mean; SD = large; scores are far from the mean. Used with interval and ratio scales
68% rule fall within the +/- 1 deviation units from the mean
bar graph use a separate bar for each piece of information. Used with nominal or ordinal data. When drawing bar graph, the bars should not touch each other
polygon (line graph) uses a line to represent frequencies, useful with interval and ratio scale variables
pie chart divide a whole circle into sections that represent relative percentages. Useful with nominal scale data
scatterplot used to visualize the relationship between the variables (correlation coefficient of +/- 1.00 - positive and negative)
null hypothesis (Ho) population means equal, the observed difference is due to random error. Logic: to be able to reject the null hypothesis --> good thing. Ho = mean of the treatment group = the mean of control group
research hypothesis (H1 or Ha) aka alternate hypothesis. Population means are not equal. The IV had an effect on the DV. Logic: to fail to reject (to accept) the research hypothesis. H1 = mean of treatment group will not equal the mean of the control group
t-value in regions of rejection (ROR) reject Ho, significant result
t-value NOT in ROR fail to reject Ho, not significant
t test used for single experiment (one IV and two levels - 2 groups). Used to examine whether 2 groups are significantly different from each other
F test ANOVA. More general and common than the t-test. Used to determine if there is a significant difference between 3 or more groups OR to evaluate the results of factorial designs
Created by: senthis1
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