HCS 202 Exam 2

Pillar 3

Population estimation with confidence intervals

single sample t test

compares a sample mean to a population mean when the population standard deviation is unknown

Variables needed for single sample t test

sample mean and standard deviation, and population mean

Robust Assumtions

must be met in order to proceed with test

Non-robust assumptions

assumptions that can be violated to some degree and still perform the test

4 Common test assumptions

independence of data, appropriate measurement variables, normality of distributions, homogeneity of variance

Independence of data

no score is linked to another, not robust

appropriate measurement variables

the variables of interest must be measured on an appropriate scale, not robust

normality of distributions

the distribution of sample means for each condition must have a normal shape, robust

homogeneity of variance

standard deviations from the sample and population are similar, robust

Null Hypothesis (H0)

states there is no effect

Alternative Hypothesis (Ha)

States there is an affect

T test null hypothesis

there is no difference between the sample and population mean

t test alternative hypothesis

there is a mean difference between the sample and population mean

if data is not compatible with the null hypothesis

fail to reject the null (insufficicent evidence)

if data is incompatible with the null

reject the null (sufficient data)

one-tailed hypothesis

only one direction of an effect or relationship is predicted in the alternative hypothesis of the test

two-tailed hypothesis

both directions of an effect or relationship are considered in the alternative hypothesis of the test

decision rule

the rule that determines when we will reject the null or fail to reject the null