Data was collected for a regression analysis where sleep quality (as a percentage) depends on the amount of caffeine consumed in a day (measured in mg). b0 was found to be 92.7, b1 was found to be -0.76, and R2 was found to be 0.86. Interpret the slope of the line. On average, when x=0, a person has a sleep quality of -0.76%. On average, each one mg increase in caffeine consumed decreases a person's sleep quality by 0.76%.
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.
Data was collected for a
- On average, when x=0, a person has a sleep quality of -0.76%.
- On average, each one mg increase in caffeine consumed decreases a person's sleep quality by 0.76%.
- On average, each one mg increase in caffeine consumed increases a person's sleep quality by 92.7%.
- On average, when x=0, a person has a sleep quality of 92.7%.
- We should not interpret the slope in this problem.
- We should interpret the slope in this problem, but none of the above are correct.
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