26. Which of these are true and which are false? Explain why the false statements are wrong.a. If two variables have a correlation of 0.3 and you add 0.1 to every value of bothvariables, then the correlation will become 0.4.b. A correlation of 0.5 means that half of the points in the scatterplot fall in a linearpattern.c. If the correlation is close to negative one, then the regression line will have a negativeslope.d. The square of the correlation coefficient tells you the percentage of the variability in Ythat is explained by knowing X.e. An outlier in the scatterplot can heavily influence a regression line.f. An outlier that falls right on the regression line can still have an important effect on thecorrelation.g. The regression line is not appropriate for making predictions when X and Y have a non-linear relationship.h. If there is a linear pattern to the data, then linear regression can be appropriately used forextrapolation.i. If there is a non-linear relationship between x and y, then the correlation will always bezero.j. The correlation r measures both the direction and strength of a straight-line relationship.k. When the correlation between two variables is nearly negative 1, then there is a cause-and-effect relationship between them.1. A correlation close to negative one indicates there were no outliers on the scatterplot.m. If there is a linear pattern to the data and there are no outliers driving the regression, thenlinear regression can be appropriately used for predictions within the range of the data.MacBook Air

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