Kin Lab Write-Up

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Null Hypothesis (Ho): There is no effect (The thing we’re trying to find evidence against) (= or < or > ) Alternative Hypothesis (H1): There is an effect (Thing we’re trying to prove) The significance level is the probability that you will say that the null hypothesis is wrong when really it is correct (Type I Error) If p-value is less than 0.05, the null hypothesis is rejected 1. Decide what you’re trying to provide evidence for: (H1). 2. Then set up the opposite as the null hypothesis and find evidence to disprove the null hypothesis. LAB Results part 2: The p-value is less than 0.05, therefore, there is a significant difference in heart rate at minute 5 of exercise for 0.5 kp vs. 2.5 kp workload on the bike. Results part 3: The p-value is greater than 0.05, therefore, there is no significant difference in heart rate at minute 5 of exercise for 0.5 kp vs. 2.5 kp workload on the bike. (Lack of significance could be due to human error). Discussion section: 1. The heart rate for minute 5 was only slightly higher than minute 1 during rest. Heart rate for minute 5 was significantly higher than minute 1 during exercise. 2. I expected both heart rate and blood pressure to increase. 3. Results were expected from heart rate. Data from blood pressure did not turn out significant, this could be due to human error. 4. The statistical analysis for heart rate at minute 5 of exercise for .5 kp vs. 2.5 kp was significant, however, analyisis for blood pressure at minute 5 of exercise turned out to be not significant. The null hypothesis for heart rate is rejected and the null hypothesis for blood pressure is accepted. We can say that there was a significant difference in heart rate at minute 5 of exercise for .5 kp vs. 2.5 kp workload on bike. Also, there was no significant difference in systolic blood pressure at minute
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