Confidence limits The upper and lower limit of what is probable at the specific

Confidence limits the upper and lower limit of what

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Confidence limits: The upper and lower limit of what is probable, at the specific probability level. Confidence intervals: A 95% CI designates the range of values within which the parameter has 95% probability of lying. *There is a 95% probability that the true population mean lies between .. and ..* Null hypothesis: States a prediction that variables in the study are not related. Type 1 error: Reject the null when it should have been accepted, false positive. Type 2 error: Retain the null when it should have been rejected, false negative. One-sample t-test: Tests whether the sample mean differs from a real or hypothesized population mean. Reject the NH when calculated t is higher than tabled t. DF=N-1. Two-tailed t-test : Uses both tails of a sampling distribution to determine the critical region (the region for rejecting the NH). One-tailed t-test: It is assumed that the value of the variables in the t-test are normally distributed in the population. Parametric tests: Assumes the DV is normally distributed in the population. Ratio or Interval. Nonparametric tests: Makes no assumptions about how the DV is distributed in the population. Chapter 6 Two-sample t-test: 2 groups are being compared. (Effect size-Cohen’s d). Cohen’s d: Standard mean difference (SMD) (d=M1-M2/PSD). (d=.20 small, d=.50 moderate, d=.80 large). Risk for type 1 error (.50), type 2 error (.20). Power: Affected by effect size; risk of a type 2 error. (p=1 – b (.20)). Preferred p=.80. higher power=more people.
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