Evaluate biostatistical methods and data


To make sound clinical decisions, you must understand how to interpret clinical research. In this project, you will be presented with several case studies where you will be required to assess the best methods for answering a clinical research question. This includes determining the data collection methods used, applying summary statistics, determining the best test to use based on the variables you are working with, assessing limitations and bias in the scenario, and performing statistical inferences. By completing this project, you practice with the process of biostatistical clinical research. You will apply these skills in Project Three, where you will make and share a clinical decision.


Provide specific evidence from at least five scholarly sources to support your claims. Use the Project One Case Studies document linked in the Supporting Materials section to complete the following:

  1. Data collection methods: Identify the different methods of data collection for each case study. Is this a quantitative, qualitative, or mixed-methods study? Explain your reasoning.

Choose one case study based on your chosen MSN track, then complete the following:

  1. Apply Descriptive Statistics: Provide the best descriptive statistics to summarize the variables and discuss why those descriptive statistics are the best to use.
  2. Testing Variables: Determine the best statistical test to examine the relationship between variables 1 and 2, 1 and 3, and 1 and 4. Discuss why this test is the best for this scenario.
  3. Investigate the Data: Assess the quality of data for reliability, validity, potential bias, and limitations.
    1. Explain two pieces of information that you would want to know to assess the reliability of the data collected and discuss the significance of those two pieces.
    2. Explain two pieces of information that you would want to know to assess the validity of the data collected and discuss the significance of those two pieces.
    3. Discuss at least two potential biases within the data.
    4. Explain two limitations of the data.
  4. Perform Statistical Inferences: State the null and alternative hypotheses and make an inference on those hypotheses based on the p value. Imagine you performed a t-test to compare mean values for variable 2 between the categories of variable 1. The p value for this test was p = 0.01. What would be the null and alternative hypotheses for this test? How would you interpret this p value?

What to Submit

To complete this project, you must submit the following:


 Your submission should be a 4- to 7-page Word document. Also include a title page. Use 12-point Times New Roman font, double spacing, and one-inch margins. Sources should be cited according to APA style.


NOTE: Case Study for reference: 

Researchers collected data from residents of a city with a population of 100,000 people to assess awareness of physical activity guidelines. Because of the difficulty of mailing surveys to people in the city, the researchers collected data from a convenience sample of 1,000 people (1%-the people who walked past city hall on a Wednesday morning). The researchers decided to focus on determining whether three factors were associated with having good or poor awareness of physical guidelines (variable 1): age (variable 2), gender (variable 3), and years of education (variable 4). Only 61% of the respondents answered the question about years of education. 


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