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