The correlation coefficient would not change, because the correlation coefficient does not depend on the order of the variables. Show The correlation coefficient, r, is given by technology or the formula shown below, where ∑zxzy is the sum of the products of the z-scores of x and y, n is the number of observed pairs in the sample, x and y are the means of x and y, and sx and sy are the standard deviations of x and y. Note that the formula for the correlation coefficient does
not depend on which variable is x and which variable is y. How do you use the regression equation to make predictions?We can use the regression line to predict values of Y given values of X. For any given value of X, we go straight up to the line, and then move horizontally to the left to find the value of Y. The predicted value of Y is called the predicted value of Y, and is denoted Y'.
Should the regression equation be used to make predictions?You can use regression equations to make predictions. Regression equations are a crucial part of the statistical output after you fit a model. The coefficients in the equation define the relationship between each independent variable and the dependent variable.
Is the use of regression line for prediction outside the interval?The use of a regression line for prediction far outside the interval of values of the explanatory variable x used to obtain the line. Such predictions are often not accurate. The least-squares regression line of y on x is the line that makes the sum of the squared residuals as small as possible.
What is linear regression how it is used to predict future values?Linear regression is one of the most commonly used predictive modelling techniques.It is represented by an equation 𝑌 = 𝑎 + 𝑏𝑋 + 𝑒, where a is the intercept, b is the slope of the line and e is the error term. This equation can be used to predict the value of a target variable based on given predictor variable(s).
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Attempting to use the regression equation to make predictions beyond the range of the data is called
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