PRESENTING RESULTS

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!

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

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