Understanding Research Results

Understanding Research Results - Chapter 13 Understanding...

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Chapter 13: Understanding Research Results: Statistical Inference Inferential statistics – used to determine whether the results match what would happen if we were to conduct the experiment again & again with multiple samples, reflect population *Difference in the sample does not show true difference (effect of IV) and random error, gives probability that the difference between the means reflects random error rather than a real difference Null hypothesis: population errors are equal, difference is due to random error, IV has no effect Research hypothesis: population means are not equal, IV has an effect Statistical significance – reject null hypothesis when we find a low probability that the obtained results could be due to random error, low probability that the difference between the means is due to random error Probability – likelihood of the occurrence of some event of outcome Alpha level – probability required for significance, usually 0.05 *Sample size determines statistical significance hence as sample increases, more confident that outcome is different from null hypothesis T-test – 2 groups difference T = group difference/ within-group variability Degree of freedom – used to select critical value One tailed test – specified direction of difference between the groups Two tailed test – no predicted direction of difference F test – 2 or more groups difference, results of factorial designs, f^2 = T, ratio of 2 types of variance
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i. System variance (between group variance) – deviation of the group means from the
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  • Spring '08
  • Psychology, Null hypothesis, Statistical hypothesis testing, Statistical significance, Statistical power, Effect size

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