A student is investigating if the amount of free time per week affects grades. He randomly surveys the students at his school and finds a linear relationship between the variables with a correlation coefficient of 0.62. Can the student conclude that more free time causes an improvement in grades? Explain. Yes. The student controlled the amount of free time, so the correlation implies causation. Yes. The student controlled the grades, so the correlation implies causation. No. The student did not control the grades, so the data only show correlation. No. The student did not control the amount of free time, so the data only show correlation.
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.
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Yes. The student controlled the amount of free time, so the correlation implies causation.
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Yes. The student controlled the grades, so the correlation implies causation.
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No. The student did not control the grades, so the data only show correlation.
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No. The student did not control the amount of free time, so the data only show correlation.
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