Inferential Statistics

• Body of statistical computations relevant to making inferences from findings based on sample observations to some larger population

• Used for hypothesis testing

Types of Hypotheses

• Research (alternative) hypothesis:– States the expected relationship or difference

between two or more variables– Published in reports/findings

• Null Hypothesis– Suggests there is no relationship among the variables

under study– Null is statistically tested– Belief in the null hypothesis continues until there is

sufficient evidence to the contrary

Hypothesis Testing/Significance Levels

• The researcher sets the significance level, or p, for each statistical test

• The degree of error the researcher finds acceptable in a statistical test

• Generally p<.05 is acceptable – 5 out of 100 findings that appear to be valid will be

due to chance– If p >.05, the finding is non-significant and null

hypothesis is retained– If p <.05, the finding is significant, null hypothesis

rejected

In reality, the null hypothesis is true

In reality, the null hypothesis is false

Use level of significance to reject null

Type I error – Null is rejected even though it is true

Decision 1 – Null is rejected when it is false

Use level of significance to retain the null

Decision 2 – Null is retained when it is true

Type II error – Null is retained even though it is false