A graphing calculator may be used wherever possible. However, you need to substa
ID: 3317065 • Letter: A
Question
A graphing calculator may be used wherever possible. However, you need to substantiate your answers for full credit. If you run out of room for your response, use the back of the page. [1)12) The operations manager of a large mail-order house believes that there is an association between the weight of the mail it receives and the number of orders to be filled. She would like to investigate the relationship in order to predict the number of orders based on the weight of the mail. From an operational perspective, knowledge of the number of orders will help in the planning of the order fulfillment process. A sample of 25 mail shipments is selected within a range of 200 to 700 pounds. Using the data with TI83/84 we obtain the following output. Input (partially shown) Output | 82399E-19 I12213095 r.9864391687 a) Find the value of the linear correlation coefficient r. c) At the 0.05 level of significance, is there evidence of a linear relationship between the weight of mail and the number of orders received? d) Predict the average number of orders when the weight of the mail is 500 pounds.Explanation / Answer
a) r = 0.98664391687
b) R-squared is a statistical measure of how close the data are to the fitted regression line. ... 0% indicates that the model explains none of the variability of the response data around its mean. 100% indicates that the model explains all the variability of the response data around its mean.
R^2 = 0.97306
This means weight of mall explains 97.31% of variation in number of orders
c) p value < 0.05
Null is rejected. Yes there is a relationship.
d) x = 500
Equation :
y = 0.191221 + 0.0297 * 500
Orders = 15.041