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# IHP 525 Milestone Three Table

Step 1: Complete the table below in which you will propose the calculations and graph(s) you will need to perform to answer the health question you are investigating.

Step 2: Provide a one- to two-paragraph explanation below as to why you chose the calculations outlined in the table above to explore your health question. Describe what statistics you will compute in order to answer your chosen health (research) question. Be sure to discuss any graphs that you will compute and what information they will provide to help you answer your health question.

I decided to used these calculation above to help answer my health question for several reasons. The Two-sample T test is useful in determing if the population between males and females are equal. T-test are

useful when two groups with different values have to be compared to one another. To complete the t-test, I would use statcrunch to calculate the mean of both genders, the standard deviation of both averages, the standard error of the sample mean, t-stat, the degrees of freedom, the significance level, and p-value. In addition, I decided to include a histogram as a visual aid, because this graph is easier to read when interpreting data that need to be compared to one another. By using a histogram, we would be able to determine if there is a relationship between gender and hospital length of stays for MI patients.

For this particular question, there are two (2) variables being considered: age and gender. These variables are utilized in grouping the females vs. males. Therefore, these are the calculations needed for this analysis:

• Frequency distribution – this provides visual representation for the distribution of observations within a particular test.
• Mean of both Samples – known as the average and we can utilized it to get an overall idea or picture of the data set. It can be best used for a data set with values that are close to each other.
• Median and Interquartile range – this make graphs of the data appear symmetrical. They also increase the influence of outlier and make the data distribute more evenly.
• Standard deviation of both averages – it provides an indication of how spread out the values are.
• Standard error of sample mean –  it validates the accuracy of a sample of multiple samples by analyzing the deviations within the means.
• Calculate t-statistic – it measures the size of the difference relative to the variation in the sample data.
• Degrees of freedom – indicates the number of independent values that can vary in an analysis without breaking any constraints.
• Significance level – the probability of rejecting the null hypothesis when it is true.
• Determine p-value from table of t-values – tells us the probability that an observed difference could have occurred by just random chance.

I will be using the two sample t test since it can tell me whether or not the means of two populations are the same. This indicates that I will be able to examine and decide whether or not the means of men and females are comparable to one another. In order for me to be able to provide a complete and correct response to the health-related inquiry, I will also need to compute the stat and the p-value. I’m going to use a histogram and a boxplot to help display the response to the question about your health. I will be able to get a clearer picture of whether or not there is a gap in the duration of stay experienced by men and girls. The variables length of service (LOS) vs gender 0 (male) and length of service versus gender 1 (female) will be included in each graph, which will result in two histograms and one boxplot. I believe that making a visual comparison of men and females will assist to illustrate the answer to the health concerns. This is because you will be able to see whether or not there is a difference between the means, as well as how the data is distributed differently between the sexes.

Choosing the above calculations, considering it is the most accurate approach to conduct this research. Testing two populations to determine whether or not which population Los varies or if each population Los is the same. I will be using various graphs to include a dot plot, histogram, and two-sample t-test. In pursuit of computing the calculations and completing graphs, I will ascertain if my null and alternative hypotheses are truthful. The two-sample t-test will establish if the proposed null hypothesis is rejected or accepted. The graphs will generate a more in-depth visual response to what the two-sample t-test displays.

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