Posted: May 22nd, 2023

Non-parametric version of the single factor ANOVA

From the descriptive statistics for the non-parametric version of the single factor and ova, it is clear they vary for individual variables and that of the paired variables. Systolic means (Fig 8) are 122.9, 132.60, and 118.80 for home, doctors’ office, and classroom respectively. It is clear the mean for the test taken at the doctors’ office is higher compared to the other two. Standard deviations are 7.094, 8.369, and 5.554 for home, doctors’ office and classroom respectively. From the result, the variation in the blood pressure taken at the doctors’ office is higher while that taken at the classroom room is the least variation. The F test value (Fig 11) is 9.964 and the significance value is 0.001, this indicates there is indeed a significant difference among the groups. To specifically pinpoint the group that differs from the other a post hoc test is carried out. From the result (Fig 13) it is clear the result taken at the doctors’ office differ from those taken in the classroom and at home, results taken in the classroom and at home do not differ.

Diastolic means (Fig 8) are 82.90, 83.20, and 82.60 for home, doctors’ office and classroom respectively. It is clear the mean for the test taken at the doctors’ office is higher compared to the other two. Standard deviations are 2.685, 3.360, and 2.675 for home, doctors’ office and classroom respectively. From the result, the variation in the blood pressure taken at the doctors’ office is higher while those taken at the classroom room and home have similar variation The F test value (Fig 12) is 0.105 and the significance value is 0.9, this indicates there is no significant difference among the groups. The post hoc test (Fig 14) confirms that as no group differs from the others.

The effect size is used to measure relationship strength between two variables in a sample or a population. It is used to complement inferential statistics in measuring the relationship strength Effect size is essential in determining the number of observations required to establish a relationship. Generally, as the size of sample size increases the statistic distribution tend to be an F distribution (Field, 2009).