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Week 3- Sampling Distributions & Hypothesis Testing
Fichas del conjunto (9)
- 1Sampling ErrorThe discrepancy, or amount of error between a sample mean and the corresponding population mean.
- 2Sampling DistributionsSampling distributions identify the degree of variability between samples we can expect by chance (i.e. due to sampling error).
- 3What is the logic of hypothesis testing?When interpreting an experimental finding, a natural question arises as to whether the finding could have occurred by chance. Hypothesis testing is a statistical procedure for testing whether chance is a plausible explanation of an experimental finding.
- 4Sample Vs Test Statistics?
- 5How is the the normal distribution used to test hypothesis??
- 6Type 1 ErrorsA type I error is the rejection of a true null hypothesis (also known as a "false positive" finding).
- 7Type 2 ErrorsA type II error is failing to reject a false null hypothesis (also known as a "false negative" finding).
- 8One-Tailed TestWhen we specify the direction we would conduct a one tailed test. Thus, the rejection region is located in only one tail of the distribution.
One tailed test: H1: μ > 900 - 9Two-Tailed TestA two-tailed test does not predict any direction. For example, a two-tailed test would be used to test the hypothesis that there is a difference between the sample mean and the population mean.
Two-tailed test: H1: μ ≠ 900
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- (Week 3- Sampling Distributions & Hypothesis Testing) HPS772- Research Methods in Psychology A Fichas sobre Week 3- Sampling Distributions & Hypothesis Testing, creado por Simon Hudson el 28/07/2018.
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- Simon Hudson
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