Warren wants to know if the amount of coffee that you drink is related to the number of hours that you stay awake. He recruits 50 participants using random sampling to report how much coffee they drank and the time of the day that they went to sleep. He then performs a correlation to determine the association between the amount of coffee that was consumed and the number of hours that they stayed awake. There was a statistically significant positive correlation between amount of coffee that participants drank and the number of hours that they stayed awake, r(49) = .82, p < .05, two-tailed, r2 = .08. This was a small effect – 8% of the variance in the amount of coffee drank is explained by hours that you stay awake (and vice versa).
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.
Warren wants to know if the amount of coffee that you drink is related to the number of hours that you stay awake. He recruits 50 participants using random sampling to report how much coffee they drank and the time of the day that they went to sleep. He then performs a
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