When homeowners list their home for sale, they begin by listing it for a price that is greater than what they expect to receive. The longer a home is on the market, without being sold, the more the price drops. A realtor selects 50 homes that are currently listed for sale. A scatterplot reveals that the association between x = the number of days the home is on the market and y = the current asking price ($) is fairly linear and can be modeled by the equation \hat{y} = 245,000-200xy^​=245,000−200x. Additionally, 85.4% of the variation in the current asking price can be explained by this linear model. Which of the following is the value of the correlation (r) for the relationship between x and y? (A) -200−200 (B) -0.924−0.924 (C) 0.1460.146 (D) 0.8540.854 (E) 0.9240.924

write a linear equation for this: "Baden, the health authority's chief financial officer stood by the veracity of that initial timeline Wednesday. He said state officials were hoping to see 200,000 to 250,000 first doses administered per week."

The amount of time adults spend watching television is closely monitored by firms because this helps to determine advertising pricing for commercials. Complete parts (a) through (d). C (a) Do you think the variable "weekly time spent watching television" would be normally distributed? If not, what shape would you expect the variable to have? A. The variable "weekly time spent watching television" is likely skewed right, not normally distributed. OB. The variable "weekly time spent watching television" is likely symmetric, but not normally distributed. O C. The variable "weekly time spent watching television" is likely skewed left, not normally distributed. O D. The variable "weekly time spent watching television" is likely normally distributed. O E. The variable "weekly time spent watching television" likely uniform, not normally distributed. (b) According to a certain survey, adults spend 2.45 hours per day watching television on a weekday. Assume that the standard deviation for "time…

The following table shows the average yearly tuition and required fees, in dollars, charged by four-year American private universities in the school year beginning in the given year. Date Average tuition 2012 $27,870 2013 $29,004 2014 $30,138 2015 $31,272 2016 $32,406 (a) Show that these data can be modeled by a linear function. For each change of 1 year in time there is an increase of $   in tuition. Find its formula. (Let d be the date in terms of number of years since 2012 and T tuition in dollars.) T(d) =  27,870+1134d       (b) Plot the data points and add the graph of the linear formula you found in part (a).         (c) What prediction does this formula give for average tuition and fees at four-year American private universities for the academic year ending in 2018?$