DillonHughes-HS345-2304A-Unit 6

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Dec 6, 2023

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Drug Therapy Trial for Lowering Heart Rate Dillon S. Hughes Department of Health Care Administration, Purdue University Global HS 345: Biostatistics Unit 5 Assignment Professor Kito Barrow November 22, 2023
Drug Therapy Trial for Lowering Heart Rate We will examine the results from a new innovative drug to help lower a patient’s heart rate. We will first exam the raw numbers form each patient group. Then we will use a statistical software to produce a t-test analysis. Finally, we will describe all of the results of the analysis. We will determine whether or not the new innovative drug was effective or not. The process for this is fairly simple. The first thing you do is collect all of your data. Next, you will run a T-Test, and write the report. The next step is to summarize the research scenario and then to justify the reason for running a t-test. At this point you would identify your hypothesis. Here you interpret the t-test results. Finally, you would provide recommendation. Our patient groups are broken up into two different groups of twenty-three. The first group, which is Group 1 was assigned a placebo. The second group, which is Group 2 was given the new innovative drug. See the table below for the raw data for each patient’s heart rate after they received their dose of medication. Group 1 Group 2 81 92 110 91 111 108 100 90 90 108 100 99 95 80 91 90 86 97 82 92 90 105 90 95 96 84 90 86 95 107 85 100 90 100 97 101
91 84 81 92 97 101 104 91 101 99 With this raw data, we produced a t-test analysis. This provided us with very valuable information. The mean for Group 1 was 93.61 and the mean for Group 2 was 95.30. The standard deviation for Group 1 was 8.29 and 7.96 for Group 2(2023). The unpaired t test showed us some interesting results. First, the two-tailed p-value equals 0.4830. By conventional criteria, this difference is considered to be statistically significant. When a p-value is smaller that means that it is less likely the results occurred by random and a stronger chance that the null hypothesis should be rejected(Mclead, 2013). The difference between the mean of Group 1 and 2 is -1.70. The t value was 0.7075 and the standard error of difference was 2.397. With our p-value being as high as it is, this leads to believe that our null hypothesis should be rejected. When a negative mean between the means in the test groups with group 2 having a lower mean, showed the medication had some effect, but a very low difference in the patients that received the medication. Any t-value grater than plus two or less than negative 2 is acceptable. Our t-value being right over 0.7 puts within the area we do not want to be in and further leading us to believe in rejecting our null hypothesis. Our standard error of difference was well above the 1.96 to -1.96, does not give us a confidence level of at lest 95%. When putting all of this data together, it is safe to assume that the null hypothesis will be rejected.
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Reference: T test calculator . GraphPad by Dotmatics. (2023). https://www.graphpad.com/quickcalcs/ttest2/ Mcleod, S. (2023, October 13). P-value and statistical significance: What it is & why it matters . Simply Psychology. https://www.simplypsychology.org/p-value.html#:~:text=A%20p %2Dvalue%20less%20than,≤%200.05)%20is%20statistically%20significant. Dun & Bradstreet. (2022, December 17). T-value . All Business. https://www.allbusiness.com/barrons_dictionary/dictionary-t-value-4942040- 1.html#:~:text=Definition%20of%20T%2Dvalue&text=Thus%2C%20the%20t %2Dstatistic%20measures,less%20than%20%2D%202%20is%20acceptable.