Business/Economics: Below is the scatterplot, regression line, and corresponding
ID: 3335909 • Letter: B
Question
Business/Economics: Below is the scatterplot, regression line, and corresponding statistics for price (x)-vs number sold (v) data. Price -vs- Demand: x Price per item (in dollars) y-Demand (number of items sold) Demand Data correlation coefficient: -0.913 regression equation: 102x + 1505 sample size: -19 2 4 " .12 sample means: x-$6.50 y= 841.1 Price per Item (in dollars) Answer the following questions regarding the relationship between price (x) and demand (y). (a) Is there a significant linear correlation between these variables? Yes No (b) What percentage of the variation in demand can be explained by the linear relation to price? Enter your answer as a percentage with one decimal place (c) How many items would you expect to sell if the price was set at $7.50? Round your answer to the nearest whole number. items Additional Materials eBookExplanation / Answer
Here r = -0.913
sample size n = 19
so, we will check the t value for the given r.
t = r * sqrt [(n-2)/(1-r2]
t = -0.913 * sqrt [(19 -2)/(1- 0.9132)]
t = -9.23
as t > tcr so we shall reject null and can say that there is significant linear correlation between these variabes.
(ii) Here r2 = 0.8336
so, 83.4% of the variation in demand can be explained by linear relation with price.
(iii) If price = $ 7.50
y^ = -102 x + 1505
y^ = -102 * 7.50 + 1505 = 740 items
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