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Statistical Inference Basics

Inferential statistics
1. Used to determine what happens if we conduct the same study multiple times
2. Statistically significant
  1. Group differences are due to random error or the variable
3. Significance level
  1. Also alpha level
  2. How willing are you to be wrong
4. Research hypothesis
  1. General hypothesis stating a relationship
5. Null hypothesis
  1. States that the population means are equal
Example statistical tests
1. T test
  1. Allows you to determine whether the mean difference came from the null hypothesis
  2. Reflect all possible outcomes if we compare the means of the two groups and the null hypothesis is true
  3. T = group difference/within group variability
  4. Degrees of freedom
    1. Adjustment used to account for the fact that we are estimating population values
2. One tailed test
  1. When the research hypothesis specified a direction of difference
3. Two tail hypothesis
  1. Research hypothesis did not specify a predicted direction of difference
4. F test
  1. Used when there are more than two levels of an independent variable
  2. Ratio of systematic and error variance
    1. Systematic variance
      1. Deviation of group mean from grand mean
    2. Error variance
      1. Deviation of individual scores from the group means
Errors
1. Type I errors
  1. When we reject the null hypothesis, but it is true
2. Type II errors
  1. When the null hypothesis is retained based on sample data, but is false
  2. Worse than Type I errors
Power analysis
1. Related to the likelihood that you will retain a null hypothesis that is false
Confidence intervals
1. When they do not overlap, the results are most likely statistically significant
Conclusion validity
1. Extent to which the conclusions on the relationships are correct

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Statistical Inference Basics

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	Created by andreaarose almost 11 years ago