QM 2 ASSUMPTIONS AND WHAT TESTS

one population test?

Parametric: one sample t test

Non-parametric: sign test or wilcoxon signed rank test

Paired/dependent samples

Parametric: paired sample t-test

Non-parametric: sign test or wilcoxon signed rank test

Two independent populations equal variances

Parametric: two sample pooled t-test

Non-parametric: wilcoxon signed rank test

Two independent populations unequal variances

Parametric: welch two sample t-test

Non-parametric: wilcoxon signed rank sum test

Assumptions for one sample t test

• data is a random sample and samples are independent

• voi is quantitative and continuous

• is measured on a ratio or interval scale

• sampled population is approximately normally distributed

Assumptions for sign test

• data is a random sample of independent observations

• VOI is quantitative or qualitative

• measurement scale is at least ordinal

Assumption for wilcoxon signed rank test

• data is a random sample of independent observations

• VOI is quantitative and continuous

• measurement scale is interval or ratio

• distribution of sampled pop is symmetric

Assumptions for matched pair sampling parametric

• data is a random sample and samples are independent pairs of observations

• voi is quantitative and continuous

• is measured on a ratio or interval scale

• sampled population of differences is approximately normally distributed

Assumptions for matched pair sampling non-parametric (wilcox)

• data is a random sample of independent observations

• VOI is quantitative and continuous

• measurement scale is interval or ratio

• distribution of sampled pop differences is symmetric

Assumptions for independent samples parametric

• data is a random sample and there are 2 independent random samples

• voi is quantitative and continuous

• is measured on a ratio or interval scale

• sampled population of differences is approximately normally distributed even though variances are unknown

Assumptions for indepenedent samples non-parametric (wilcox)