Statistical and the t-test methods
Milestone 3 table
| Question: | Answer: |
| The research Question | The research question is set to determine the extent to which MI patients vary by their follow up status according to their age. |
| The corresponding alternative and the null hypothesis | The null hypothesis H0: There is the absence of statistically substantial variance in the follow up status of the MI patients according to their gender. H0:µ1= µ 2 Ha: Significant difference in the follow up status of MI patients according to age. Ha: µ=/= µ 2 |
| Descriptive statistics to compute, its variable(s), that assists in the question | I need two variables, that is the status follow up and age. Because the question is mainly concerned with disparities in follow up status and age, the follow up status will be put into two groups of made follow ups vs. Lower follow ups. The age will be categorized into 1. Frequency 2. Median and Interquartile range 3. The mean for the two samples that is sample 1 and sample 2 4. The standard deviations that the two averages achieve. 5. The sample mean standard error 6. T- statistic is calculated 7. Degrees of freedom 8. Significance level 9. P-value should be determined from the tables of t-values. |
| The name of the statistical test used in the hypothesis which answers the health question | 2 sample t-test |
| Formula for the chosen statistical test | t = [ (x-bar1 – x-bar2) – d ] / sqrt[(s1^2/n1) + (s2^2/n2)]
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| The reason for the statistical test chosen to be appropriate for this health question. | To test the difference between the two populations, a two-sample t-test is used. The t-test will assist in comparing the age data between the young MI patients, which will be sample 1 and old MI patients, which will be sample 2. |
| The best graph that can be used to visualize the answer to the health question meant for different subgroups of subjects | A histogram that carries the largest number of follow up status in the vertical axis and age categories on the horizontal axis. |
Step 2
To compare whether two groups have different average values, the two-sample t-test is used. Because I will be calculating the average follow up status difference amongst the young MI patients and the older MI patients. The two-sample t-test is an excellent way to get the calculations right. To complete the t-test, the mean of both follow up status samples should be calculated, the standard error of the sample mean, and the mean of both age samples. The significance level, the degrees of freedom, and the p-value are also calculated. In addition to using the t-test in conducting the study, two histograms should be included for both follow up status indicating the frequency placed on the vertical axis and the ages at the horizontal axis. The use of histograms helps in comparing the skew and shape of the follow up status of the patients to assist in visualizing the significant difference between the young and old patients.