Descriptive Statistics for In

This week, we have read and discussed how we analyze and interpret research once we have collected our data. This is helpful for multiple reasons: 1. We learn how to conduct statistical tests, 2. We learn how to write and interpret these statistical tests, 3. We learn how to interpret and evaluate tests completed by other researchers.

Instructions: We will first practice conducting descriptive statistical tests and second practice how to write the analyzed tests and interpret analyzed research:

  • In the first section, you will use the excel spreadsheet provided to conduct a test for: 1. Central tendency, 2. Shape, and 3. Dispersion.
  • In the second section, I will provide 2 examples of hypothetical research findings for you to write the results of the descriptive statistics. You will complete the following:
    • Write two sentences that articulates the results of the statistical tests
    • Interpret and explain what the central tendency result means, what the shape of the distribution means, and dispersion means.

Section 1: Conducting your own descriptive statistics:

  • Download the excel spreadsheet or upload it to good sheets. Create an average score for each participant. Based on these average scores, conduct 3 descriptive statistical tests. One test for central tendency, one to determine the shape, and one to test for dispersion.
  • Isabelle recently conducted a survey that assessed the difference between mask-wearing behavior between those rural and metropolitan areas within the United States. Isabelle received 100 completed surveys (50 people from metropolitan areas and 50 people from rural areas). Participants were asked several questions using a 5-point Likert scale. Higher numbers suggest more frequent behavior for wearing masks.
  • James and his colleagues were hired by Stanford Health Care to examine how comfortable patients feel about disclosing health discomfort to their healthcare providers. They believed there is an age discrepancy between patients. Therefore, James and his colleagues conducted a survey with a Likert scale of 1-7. Higher numbers suggest higher comfortability disclosing to their healthcare providers.

Section 2: Writing and making sense of statistical results:

Metropolitan Mean: 4.3

Rural Mean: 2.9

Metropolitan Skew: 0.8

Rural Skew: 0.3

Metropolitan Standard Deviation: 0.7

Rural Standard Deviation: 1.6

James and his colleagues received 322 completed surveys. 103 were aged 18-36 and were labeled as the younger group. 127 were aged 37-55 were labeled as the middle group. 92 participants are aged 56-88 and were labeled as the elderly group. Descriptive results were conducted and were:

Young Mean: 2.3

Middle Mean: 5.6

Elderly Mean: 6.3

Young Median: 2.1

Middle Median: 5.6

Elderly Median: 6.2

Young Standard Deviation: 0.4

Middle Standard Deviation: 2.1

Elderly Standard Deviation: 1.0


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