Psych stats quiz for chap 8 and 9
Terms in this set (20)
As the sample size increases, the standard error decrease.
If the researcher hypothesizes that a treatment will decrease scores, then the critical region for a directional test will be in the right tail.
Most researches would like to reject the null hypothesis.
If the sample data are in the critical region with a= 0.05, then the same sample data would still be in the critical region if a were changed to 0.01.
In general, the null hypothesis states that the sample mean does not differ from the population mean.
Type II error occurs when we set a low a too low.
The critical region for a hypothesis test consists of sample outcomes that are very unlikely to occur if the null hypothesis is true.
Type 1 error occurs when a researcher concludes concludes that there is no effect when there really is an effect.
An alpha level of 0.05 has a smaller critical region than an alpha level of 0.01.
In a hypothesis test, the value obtained for the z score is independent of (not affected by) the sample size
As the sample size is increased, the distribution of t statistics becomes flatter and more spread out.
As degrees of freedom (df) increases, the t value in the t distribution table also increases.
Sample size has no influence on effect size.
The t distribution for df=4 is flatter and more spread out then the t distribution for df =20.
The confidence interval always includes the population mean
For a hypothesis test using a t statistic, boundaries for the critical region will change if the sample size is changed.
A t statistic is used when population variance is known.
Two samples from the same population will have different t statistics even if they are the same size and have the same mean.
The confidence interval always includes the sample mean.
If other factors are held constant, the bigger the sample is, the greater than likelihood of rejecting the null hypothesis.
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