Hello Professor and Class,

Week #3-Hypothesis Testing Method in Statistics.

Hypothesis testing is a structured statistical process used to determine whether sufficient evidence exists to support a claim about a population parameter. As described in The Visual Learner: Statistics, the process begins with stating a null hypothesis and an alternative hypothesis, which are then tested using sample data. A hypothesis is a statement about the value of a population parameter, and the goal is to decide whether the hypothesis is likely true or false based on probability (Triola, 2009).

As a Medical Laboratory Scientist, in both my current and future employment, I would like to conduct a research study in a clinical laboratory focused on venipuncture success rates. Specifically, the study would examine whether experienced phlebotomists achieve a higher first-attempt success rate when drawing blood compared to less experienced staff.

Null Hypothesis (H): There is no difference in first-attempt successful blood draws between experienced phlebotomists and less experienced phlebotomists.

Alternative Hypothesis (H): Experienced phlebotomists have a higher first-attempt successful blood draw rate than less experienced phlebotomists.

A Type I error would occur if the study concludes that experienced phlebotomists have a higher success rate when, in reality, there is no true difference between the two groups. This could lead to incorrect staffing decisions based on false assumptions. A Type II error would occur if the study fails to detect a real difference in success rates when one actually exists, possibly due to a small sample size or data variability.

This study would use a one-tailed test because the alternative hypothesis predicts a specific direction of effectthat experienced phlebotomists perform better, not just differently. Understanding and correctly applying hypothesis testing is essential in laboratory research to improve patient outcomes and ensure evidence-based practice (Triola, 2009; Polit & Beck, 2021).

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-Patricia Asturias-Escobar

References:

Polit, D. F., & Beck, C. T. (2021). Nursing research: Generating and assessing evidence for nursing practice (11th ed.). Wolters Kluwer.

Triola, M. F. (2009). Elementary statistics (10th ed.). Pearson Education.

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