regression slope (beta). We
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.
![A least-squares regression line for a set of data with dependent variable y and independent variable x produces a 95% confidence interval [-0.5,1.8]
on the regression slope (beta). We can conclude that:
the predicted value of y for a given x will lie in the range [-0.5x,1.8x] 95% of the time
the regression slope must be zero
O beta will fall inside the range [-0.5,1.8] 95% of the time
The data show no evidence of a linear relation between x and y
O none of these](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb160e02c-3877-4472-9a23-f9424203efc1%2F2f743c44-3da8-4b75-ae0f-fe4ddd7779ad%2F6ckjimug_processed.jpeg&w=3840&q=75)
the regression slope (beta) value fall under confidence interval
Yi=β0+β1 Xi+εi
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