Math

Basic Statistics Data Used in Everyday Life

Discussion

Required Resources

Read/review the following resources for this activity:

· OpenStax Textbook: Chapter 1

· Lesson 1 Reading

· Minimum of 1 scholarly source AND one appropriate resource such as the textbook, math video and/or math website

In your reference for this assignment, be sure to include both your text/class materials AND your outside reading(s).

Initial Post Instructions

1. Present two different types of data, or variables, used in the health field. Examples could be blood pressure, temperature, pH, pain rating scales, pulse oximetry, % hematocrit, minute respiration, gender, age, ethnicity, etc.

2. Classify each of your variables as qualitative or quantitative and explain why they fall into the category that you chose.

3. Also, classify each of the variables as to their level of measurement–nominal, ordinal, interval or ratio–and justify your classifications.

4. Which type of sampling could you use to gather your data? (stratified, cluster, systematic, and convenience sampling)

Follow-Up Post Instructions

Respond to at least one peer. Further the dialogue by providing more information and clarification.

Your responses to other students can explain additional analyses that could be done with the variables they selected. Consider confounding variables, discrete or continuous data, the effects of outliers, etc.

Course Outcomes

CO 1: Given scenarios supported by population data, apply sampling techniques and explain potential pitfalls and bias in data collection.

CO 2: Given datasets with qualitative and quantitative data, differentiate between the types of data and how they can be applied in statistical studies for everyday life.

**Remember to use the Chamberlain Library (

https://library.chamberlain.edu/home
) to research scholarly resources to provide evidence in your discussions and cite your references at the end of each post. Your initial post is encouraged by 11:59 pm MT Wednesday, and your one follow-up post is due by 11:59 pm MT Sunday.**