A correlation of zero between two quantitative variables means that there is no association between the two variables. we have done something wrong in our calculation of r. there is no linear association between the two variables. re-expressing the data will guarantee a linear association between the two variables.

A team from UNHABITAT took a random sample of 230 households in a city to better understand how the size of a house (measured in metres) is related to the number of people living in that house. They performed a regression analysis on the data and found that regression model had an R² = 18.3%. What is the correlation between the size of a house and the number of people living in that house? 0.667 0.183 0.033 0.904 0.428

When the heights (in inches) and shoe lengths (also in inches) were measured for a large random sample of individuals, it was found that r = 0.89, and a regression equation was constructed in order to further explore the relationship between shoe length and height, with height being the response variable. From this information, what can we conclude? The correlation coefficient should have no units. The regression equation relating shoe length to height must have a slope equal to 0.89. The regression equation relating shoe length to height must have a positive intercept. O Approximately 89% of the variability in height can be explained by the regression equation. Because the value of r is less than 1, we should characterize this relationship as being weak.

From a regression equation r2= 0.39 and the slope = -2.8 What is the linear correlation coefficient r?