Diabetes Costs and SLR
Linear regression allows you to predict an unknown outcome from known data, based on the strength of the relationship.
How would you use a simple linear regression analysis of diabetes costs to help with treatment of diabetes?
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Learning Components
This activity will help you achieve the following learning components:
Practice interpreting statistical data.
Demonstrate statistical literacy by using correct statistical terminology.
Practice academic writing skills in discussions
Hypothesis Testing: Correlation and Simple Regression
Assignment Overview
In this assignment, you are given data to determine the relationship between pairs of variables.
Based on the descriptive data, you will choose the appropriate correlation analysis and interpret the strength and direction of the correlation and its statistical significance. Note: For some of the correlation pairs, it is appropriate to examine the ability to predict one variable from the other.
To successfully complete this assignment, you must address the following:
Describe the types of relationships that can occur between two variables.
Determine which correlation analysis is appropriate, based on the type of data collected.
Describe the information that can be gleaned from a correlation analysis.
Describe the role of linear regression analysis.
Interpret a simple linear regression output.
Preparation for the Assignment
The following files must be downloaded from Resources to complete this assignment:
Correlation and Simple Regression Tables Template (includes Data Description).
Unit 8 SPSS Output [PDF].
Instructions for the Assignment
Step 1: Data Validation
As with all new data sets, your first step is to do the data validation.
Review the Unit 8 SPSS Output [PDF] and note any issues with the data.
Step 2: Correlation
Establish the relationships of the variables using the following correlation procedures. Based on your data validation, choose the appropriate correlation coefficient and interpret the strength, direction, and significance of the correlation for six variable pairs of your choice.
Review both the Pearson correlations (parametric) and the Spearman rank-order correlations.
Step 3: Simple Regression
Interpret the appropriate simple regression results for your variables.
Additional Requirements
Create a document that is clearly written and generally free of grammatical errors.
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