10 -5 + - 10 + 100 125 150 175 200 Predicted Residual
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 researcher analyzing somedata created a linear model
with R2 = 94, and having the residuals plot seen here.
What should she conclude?A) The linear model is appropriate, because about the
half the residuals are positive and half negative.
B) The linear model is appropriate, because the value of
R2
is quite high.
C) The linear model is not appropriate, because the value
of R2
is not high enough.
D) The linear model is not appropriate, because the
residuals plot shows curvature.
E) The linear model is not appropriate, because the
residuals plot identifies an outlier.
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