Each month, a government agency releases its latest estimate of construction activity in the housing industry. A key me
Posted: Wed May 11, 2022 11:17 am
Each month, a government agency releases its latest estimate of
construction activity in the housing industry. A key measure is the
percentage change in the number of new homes under construction.
Does the release of this number come with a change in the stock
market? The accompanying data show the percentage change in the
number of new, privately owned housing units started each month,
as reported by the government agency. The data also include the
percentage change in the S&P 500 index on the same day the
government agency releases the housing results.
(b) Find the correlation between the two variables in the
scatterplot. What does the size of the correlation suggest about
the strength of the association between these variables?
r=enter your response here
(Type an integer or decimal rounded to three decimal places as
needed.)
Data table Full data set Percent Change of Percent Change All Private Starts of S&P 500 - 0.70671 0.13485 11.00218 0.69842 6.40420 0.56293 5.03721 -1.56465 3.39540 - 1.01325 0.19950 0.36194 0.54970 -0.79900 -7.93420 -0.44074 - 2.08851 0.69168 8.32421 0.22357 -0.14670 - 1.18570 - 17.58636 0.60107 Percent Change of Percent Change All Private Starts of S&P 500 -9.90000 - 1.88101 - 6.03960 -0.96659 -2.18845 -3.02718 - 1.27764 -0.77765 - 10.97695 0.43499 3.73993 -1.23169 -2.71386 -0.15816 2.41400 -0.81471 0.16243 -0.67853 1.46341 0.27349 -3.63112 0.54648 - 5.41363 0.65777
(b) Find the correlation between the two variables in the scatterplot. What does the size of the correlation suggest about the strength of the association between these variables? The correlation r is a measure of the strength of the linear association between two quantitative variables. The formula below can be used to find the correlation. Recall that x is the mean of the explanatory variable, sy is the standard deviation of the explanatory variable, y is the mean of the response variable, sy is the standard deviation of the response variable, and n is the number of cases. (x1-x) (y1 - y) + (x2 -x) (y2-y) +...+ (xn->) (yn-y) ) cov(x,y) = cov(x,y) r = corr(x,y) = Susy First solve for the covariance. Begin by finding the means of x and y, in this case the means of the percentage change in the number of new housing units started and the percentage change in the S&P 500 index, respectively, rounding to three decimal places. + + n-1
construction activity in the housing industry. A key measure is the
percentage change in the number of new homes under construction.
Does the release of this number come with a change in the stock
market? The accompanying data show the percentage change in the
number of new, privately owned housing units started each month,
as reported by the government agency. The data also include the
percentage change in the S&P 500 index on the same day the
government agency releases the housing results.
- Each Month A Government Agency Releases Its Latest Estimate Of Construction Activity In The Housing Industry A Key Me 1 (21.62 KiB) Viewed 21 times
scatterplot. What does the size of the correlation suggest about
the strength of the association between these variables?
r=enter your response here
(Type an integer or decimal rounded to three decimal places as
needed.)
- Each Month A Government Agency Releases Its Latest Estimate Of Construction Activity In The Housing Industry A Key Me 2 (23.61 KiB) Viewed 21 times
(b) Find the correlation between the two variables in the scatterplot. What does the size of the correlation suggest about the strength of the association between these variables? The correlation r is a measure of the strength of the linear association between two quantitative variables. The formula below can be used to find the correlation. Recall that x is the mean of the explanatory variable, sy is the standard deviation of the explanatory variable, y is the mean of the response variable, sy is the standard deviation of the response variable, and n is the number of cases. (x1-x) (y1 - y) + (x2 -x) (y2-y) +...+ (xn->) (yn-y) ) cov(x,y) = cov(x,y) r = corr(x,y) = Susy First solve for the covariance. Begin by finding the means of x and y, in this case the means of the percentage change in the number of new housing units started and the percentage change in the S&P 500 index, respectively, rounding to three decimal places. + + n-1