Essay on Hlt 362v Exercise 29

So, we should reject the null hypothesis H0. At a 0.05 level of significance level, we conclude that there is a significant difference between the average height for females and the average height for the males.

·  What conclusions did the study reach? Are the conclusions appropriate? Why or why not?

7. If a study had a result of F(2, 147) = 4.56, p = 0.003, how many groups were in the study, and what was the sample size?

Reporting t values- when you have already reported p values- is not necessary and can cause confusion.

An alpha level of 0.05 is arbitrary and was set as a standard by scientists. One of the key concepts in hypothesis testing is that of significance level or, the alpha level, which specifies the probability level for the evidence to be an unreasonable estimate. Unreasonable means that the estimate should not have taken its particular value unless some non-chance factor(s) had operated to alter the nature of the sample such that it was no longer representative of the population of interest. (Price, 2000)

Gender – whether there was a difference in performance between genders; used for comparison between male and female participants

It tells that the t-statistic with 97 degrees of freedom was 2.14, and the corresponding p-value was less than .05, specifically around 0.035. Therefore, it is appropriate to conclude the research study was statistically significant.

However, treatment four, 0.1296 (±0.608), represents that the mean was extraneous from what it should be (Table 1). The t-tests show how different the mean is in each treatment.

9. If there were 32 subjects in the experimental group and 36 subjects in the control group, why is the income data only reported for 30 subjects in the experimental group and 34 subjects in the control group? Based on the “Note” at the bottom of Table 1, Numbers do not always total 32 for the experimental group or 36 for control group because of missing data.

| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are

With a P-value of 0.00, we have a strong level of significance. No additional information is needed to ensure that the data given is accurate.

The t value tells us about the differences between men and women post MI physical component score. In my practice using this t value, I would be able to work differently between men and women after post MI. Teaching might provide to women more about physical functioning, role physical, bodily pain and general health since these are all included in physical component score. The physical component score for women is 48.5 compared to men 51.1 (standard deviation). Therefore, women might need to educate more about the

For this independent t test, the mean GPAs of 64 females and 41 males were compared. The variables used are (1) gender, and (2) GPA. The predictor, or independent, variable is gender. And the outcome variable is GPA. Gender can only have two values, male or female; this

In this case, level of significance, α was not provided. Therefore, the analysis will be evaluated based on two α values which are:

There were also issues with the groups of participants that took part in the study because there were three groups, T1, T2, and T3, that were involved in the study, but not all of the groups were tested for all conditions of the study and there were different numbers of participants in each group as well. Though T2 and T3 stemmed from T1, the groups still had different number of participants because of the lower response rates (Iyengar, Wells, & Schwartz, 2006). Lastly, a