Statistical Test and Hypothesis Assignment Paper

Statistical Test and Hypothesis Assignment Paper

Statistical Test and Hypothesis Assignment Paper

Statistical tests are essential when one wants to use sampled data in concluding a bigger population because these tests always account for some percentage of error. The choice of the statistical tests depends on the variables that a researcher would want to examine (Amrhein et al., 2019). Therefore, hypothesis testing is about testing an assumption regarding a population parameter.

Statistical tests use levels of significance and p-values to determine whether to accept or reject the null hypothesis. The rejection of the null hypothesis improves the chances that one will be making a correct conclusion about a study (Andrade, 2019). The choice of the hypotheses comes from comparing the statistical value to the critical value. For example, the null hypotheses would be rejected if the statistic falls into the rejection region. If the statistic value is (>1.96) or (<1.96), the researcher will reject the null hypothesis.

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In testing whether the use of an infection bundle or lack of one helps prevent/decrease CLABSI, the results from the choice of the statistical tests applied would choose whether the use of an infection bundle prevents or decreas CLABSI. In this case, the hypothesis will adopt the following design if t-tests were done to test the significance;

H₀: Use of infection bundle does not significantly contribute to the prevention of CLABSI

H₁: Use of an infection bundle significantly contributes to the prevention of CLABSI.

From these results, the null hypothesis will be rejected if p < .05 and the alternative hypothesis accepted. At the α = 0.05 level of significance, there is enough evidence to conclude that the use of infection bundles significantly contributes to the prevention of CLABSI. However, if the output on the statistic summary will show p >.05, then the null hypothesis would be accepted, and the conclusion made that use of infection bundle does not significantly contribute to the prevention of CLABSI. Statistical tests are the basic source of choice in healthcare. The computation of the statistical values allows the researcher to reject or accept a null hypothesis. The process starts by forming the hypothesis statement that will guide a person in rejecting or accepting the null hypothesis the above case on CLABSI.

References

Amrhein, V., Trafimow, D., & Greenland, S. (2019). Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. The American Statistician, 73(sup1), 262-270. https://doi.org/10.1080/00031305.2018.1543137

Andrade, C. (2019). The P value and statistical significance: misunderstandings, explanations, challenges, and alternatives. Indian Journal of Psychological Medicine, 41(3), 210-215. https://doi.org/10.4103%2FIJPSYM.IJPSYM_193_19

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How can the statistical test of (hypothesis) help to draw conclusions about whether the use of an infection bundle or lack of one help to prevent/decrease CLABSI?