After performing a statistical regression on a set of data, the value of the correlation coefficient r was -0.8981. What does that imply about the data? There is a strong positive linear correlation between the variables. There is a strong negative linear correlation between the variables. There is a strong positive non-linear correlation between the variables. There is a strong negative non-linear correlation between the variables. There is almost no correlation between the variables (the data is scattered).
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In this case, the value of r is -0.8981, which is close to -1. A negative value of r indicates a negative linear relationship between the variables. Since the value of r is close to -1, it implies that there is a strong negative linear correlation between Show more…
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The linear correlation coefficient for a sample of bivariate data of size n=37 is found to be r=-0.825. Which of the following conclusions can be drawn? - There is a negative correlation between the variables. - There is no significant correlation.
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Plot the points and determine whether the data have positive, negative, or no linear correlation (see figures below). Then use a graphing utility to find the value of $r$ and confirm your result. The number $r$ is called the correlation confficient. It is a measure of how well the model fits the data. Correlation coefficients vary between $-1$ and $1,$ and the closer $|r|$ is to $1,$ the better the model. (GRAPH NOT COPY) Positive correlation Negative correlation No correlation $$ (1,7.5),(2,7),(3,7),(4,6),(5,5),(6,4.9) $$
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