1. PRESENTING RESULTS

2. Presenting results
State statistical hypothesis along with your scientific hypothesis
Use flowchart to show experimental design
Show how replication, control and randomization are used
Show both exploratory data analysis and inferential analysis
Discuss meaning of graphs and measures
State level of significance in tests (p-value)
State conclusions of tests
State the statistical and practical significance of results
Tell whether null hypothesis was accepted or rejected
Statistics are meaningless if they are misrepresented or misunderstood!

3. Writing t-test results
“An independent–sample t-test was used to check the effectiveness of Drugesterol in reducing cholesterol, t(99) = 0.33, but no significant difference was found (Drugesterol M = 34; Control M = 36).”
type of t-test
degrees of freedom (n-1)
p-value
≥ 0.05
means of experimental groups

4. Writing t-test results
“An independent–sample t-test was used to check the effectiveness of Drugesterol in reducing cholesterol, t(99) = 2.10, with Drugesterol associated with lower cholesterol than the control condition (Drugesterol M = 34; Control M = 36).”
type of t-test
degrees of freedom (n-1)
p-value
< 0.05
means of experimental groups