Statistics > Research Paper > Grand Canyon UniversityDATA ANALY DNP 830DNP 830 Assignment Week 2 What are the data saying? (All)

Grand Canyon UniversityDATA ANALY DNP 830DNP 830 Assignment Week 2 What are the data saying?

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What are the data saying? Amber L. Morgan Grand Canyon University: DNP 830 February 4, 2021Introduction Research studies often record quantitative data results. Interpreting this data is very important to fully understand the results and how they impact the research question. Viewing raw data often does not demonstrate the true meaning. Statistical analysis of the collected data can help provide a proper understanding of what the data are saying. Statistics takes the individual pieces of information, performs analysis depending upon the desired results, and are often displayed in a table, chart, or graph form. This paper aims to review varying statistical analysis methods utilizing a sample database. Statistical Tests Paired Sample T-Test A Paired Sample t-etst compares two means from the same sample to determine if there is a significant difference. This test is often used in studies containing designs such as pretest/posttest, control/experimental, or samples from the same subject on different sides. Paired Sample ttests help compare the difference between two points in time, two conditions, two measurements, or a matched pair. This test is a parametric test and cannot be used on unpaired data, more than two units, not normally distributed data, or a ranked outcome. In this example, baseline weight is compared to intervention weight to determine if a significant difference exists for all that partook in the study. This test will examine a change in weight for both the intervention and nonintervention groups. The mean baseline weight is calculated at 217.5 pounds with a standard deviation of 53.40, and the intervention weight is 178.3 pounds with a standard deviation of 44.88. The results include t=7.188 with df=29, t(df)=2.05 with a 95% confidence interval and p=0.000. A p<.005 indicates a statistically significant difference. Independent Sample T-Test 2An Independent Sample t-Test is a parametric test that evaluates whether two populations have the same mean on a given variable (Kent State University, 2021). This test is often used to assess the differences between the means of two groups, the means of two interventions, or the means of two change scores (Kent State University, 2021). Data must contain a continuous dependent variable, a categorical independent variable of two groups or more, include unrelated subjects in the various groups, use a random sample with a normal distribution of the dependent variable, approximately equal variances across groups, and no outliers. Typically, each group should contain a minimum of six participants and have the same number of subjects in each group. In the example, this test was chosen to evaluate the differences between the two intervention groups' mean weight. The results include intervention mean weight of 218.3 pounds with a standard deviation of 53.84 and baseline mean weight of 216.7 pounds with a standard deviation of 54.8, p=0.934, and t(28)=0.084 with a 95% confidence interval, assuming equal variances. A t=0.084 is less than the critical value of 1.074, indicating that the results are not statistically significant. The mean of intervention weights and the mean of baseline weights could be caused by sampling variability.

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