Hello,

This is my problem:

John is interested in determining if frequency of exercise affects pulse rate. John randomly samples 55 individuals at a local gym and divided them into three (3) groups of exercisers: 1 = high frequency, 2 = moderate frequency, and 3 = low frequency. After their workout, John measured their pulse rate. Our team will analyze whether a relationship exists between exercise frequency (Exercise) and pulse rate (Pulse 1).Our team formulated a null hypothesis and an alternative hypothesis.We conducted a relationship analysis of the data using a one-way ANOVA (as well as Tukey's HSD post hoc tests).In the process, we will identify the F ratio for the group effect, sums of squares for the exercise effect, mean for moderate exercisers, and P value for exercise effect.

Hypothesis

Null hypothesis:

Ho: There is no significant relationship between high frequency, medium frequency, and low frequency exerciser's pulse rates. (H_o: _{1 = 2 = 3}).

Alternative hypothesis:

Ha: There is a significant relationship between high frequency, medium frequency, and low frequency exerciser's pulse rates. (H_a: _{1 2 3}).

My ANOVA test came out with these results:

Anova: Single Factor

= .05

SUMMARY

High Frequency:

Count: 6

Sum: 445

Average: 74.17

Variance: 174.57

Medium Frequency:

Count: 33

Sum: 2452

Average: 74.30

Variance: 128.41

Low Frequency

Count: 16

Sum: 1242

Average: 77.63

Variance: 66.12

ANOVA

Source of Variation

SS df MS F P-value F crit

Between Groups 126.88 2.0 63.44 .55 .58 3.18

Within Groups 5973.55 52.00 114.88

Total 6100.44 54.00

First of all, did I break this down into groups correctly?

Second, with a high P-value of 0.58 (substantially greater than the 0.05 criterion, am I correct that it is not necessary to perform a Tukey-Kramer analysis?

Thank you in advance!\