Study 3: Age & Pain. Using the same data set PillShapeColor - use Pearson Correlation and simple linear Regression to create results and then summarize these in APA-style. Run a Pearson Correlation on age and pain rating. Create a scatterplot with pain rating on Y and age on X axis. Run a simple linear regression model with pain rating as DV and age as IV. Regression → Linear Regression, choose your DV, IV(s) –use defaults settings. 1-What is the equation for the regression line? How much variance in pain is accounted for by age (R2)? Interpret this in context of the study (is this a lot of variance explained or not much). 2-Describe the regression results simply and clearly- include the slope and constant and describe what the slope means. Is age a significant predictor of perceived pain? Finally, describe what the model predicts about the pain rating of a person who is 40 years old and someone 70 years old.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Study 3: Age & Pain.
Using the same data set PillShapeColor - use Pearson
- Run a Pearson Correlation on age and pain rating. Create a
scatterplot with pain rating on Y and age on X axis. - Run a simple linear regression model with pain rating as DV and age as IV.
Regression → Linear Regression, choose your DV, IV(s) –use defaults settings.
1-What is the equation for the regression line? How much variance in pain is accounted for by age (R2)? Interpret this in context of the study (is this a lot of variance explained or not much).
2-Describe the regression results simply and clearly- include the slope and constant and describe what the slope means. Is age a significant predictor of perceived pain? Finally, describe what the model predicts about the pain rating of a person who is 40 years old and someone 70 years old.
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