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Inferential statistics:. 1. Techniques for making generalizations from samples. Hypothesis testing:. 1. Determining if the sample is representative enough of the population so that an inference can be made. 5-step process for refuting chance (sampling error):.
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Inferential statistics: • 1. Techniques for making generalizations from samples.
Hypothesis testing: • 1. Determining if the sample is representative enough of the population so that an inference can be made.
5-step process for refuting chance (sampling error): • 1st. Identify the characteristics of data collected, I.e., variables
2nd State your hypothesis: • (a) research or alternate hypothesis, i.e., the expected relationship • (b) null hypothesis, i.e., statement of no relationship, no association, or independence
3rd Select sampling distribution: • Use a Z distribution, whenever N is greater than 120 • Use a t distribution whenever N is 120 or less 3. Use a one-tail test—if the direction of the difference can be predicted 4. Use a two-tailed test—if direction cannot be predicted
4th calculate test statistic: Calculate the outcome for your sample, e.g., regression, chi-square etc.
Level of Significance: • The probability of drawing by chance an unlikely sample outcome. You can set the alpha at any level, but the convention is to set at .01 or .05 2. Alpha = .01 means 1 out of 100 samples(times) you would be wrong to conclude that the sample differs from the population 3. Alpha = .05, i.e., 5 out 100 samples, etc
Critical region: 1. Rejection region. Once alpha level is selected, you can determine the sample outcome that begins the critical region by using the table--
5th make decision on null and research hypotheses: • Decision on Ho: • [ ] Reject a null hypothesis—means chance of an incorrect decision, I.e., type 1 error—is equal to the alpha level you have selected • [ ] accept (fail to reject) means chance of type 2 error
Decision on research on research hypothesis: 1. Ha= is there a statistically significant difference? yesno [ ] reject [ ] accept * If you accept then you can conclude that there is a statistically significant difference 2. Note: you would either conclude that the sample is or is not representative of the population from which it was drawn. Implications--