Statistical Concepts in Healthcare

Statistical Concepts in Healthcare

It has long been a requirement for health care workers to take an Introduction to Statistics class. Why is it important for a person working in health care to understand statistical concepts? To answer this question, please provide two specific examples incorporating two different statistical terms from “Visual Learner Statistics,” located in the Topic 1 Resources. Do not use the same examples as those in a prior post. You may reference other articles in this topic or conduct your own scholarly research if more statistical terms are needed.

Initial discussion question posts should be a minimum of 200 words and include at least two references cited using APA format. Responses to peers or faculty should be 100-150 words and include one reference. Refer to “HLT-362V Discussion Question Rubric” and “HLT-362V Participation Rubric,” located in Class Resources, to understand the expectations for initial discussion question posts and participation posts, respectively.

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Statistical Concepts in Healthcare

Importance of Understanding Statistical Concepts in Healthcare

It is critical for healthcare workers to understand statistical concepts because they frequently rely on data to make informed decisions that directly impact patient care, treatment outcomes, and resource management. By interpreting and applying statistical principles, healthcare workers can assess clinical practices, identify trends, and evaluate treatment efficacy. Two key statistical terms that are especially relevant to healthcare workers are confidence intervals and correlation coefficients. Statistical Concepts in Healthcare

1. Confidence Interval: A confidence interval is a range of values that is used to estimate the true value of a population parameter with a certain level of confidence. For example, in clinical trials, researchers use confidence intervals to estimate the effectiveness of a new drug. If a study finds that the drug reduces symptoms in 70% of patients, the confidence interval might be between 65% and 75%. This means that the true effect of the drug is likely to fall within this range, and the healthcare provider can use this information to make informed decisions about whether or not to recommend the drug to patients (Field, 2013).
2. Correlation Coefficient: The correlation coefficient is a statistical measure that describes the strength and direction of a relationship between two variables. For instance…