We have 2 sets of numbers, we found the line of best fit to be: y = 10x+5. Using that information, we made a prediction when x = 12, y = 125. What can w say about the prediction? Check all that apply: Errors in regression prediction are quantified by R squared and the standard error of the estimate. With a value of slope of more than 1, we should always trust the prediction. That prediction is made correctly. This regression is based on a curve. For an increase of 10 on the y, we increase 5 on the x. We shouldn't trust in that prediction because we don't know what the error is.
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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