Question 1) Suppose you are interested in studying the relationship between the temperature of a particular day and the number of customers that a large ice cream shop serves on that day. To do this you randomly choose 11 days to visit the shop and record both the high temperature of that day and how many customers it served for the entire day. You get the following data: High Temperature (in ° F) 75 83 92 77 92 86 73 96 85 88 80 Number of Customers 430 480 600 400 510 520 370 590 590 520 430 (a) Draw a scatterplot for this data. Make sure to label your axes. (b) Calculate the correlation coefficient, and decide if there is enough evidence for a correlation. (c) Construct the LSR for this data. Keep one decimal place for the slope and round the intercept to the nearest whole number. (d) Graph the LSR on your scatterplot. (e) Write a sentence interpreting the slope of the LSR. (f) How many customers does your model predict will show up on day where the high temperature is 50° F? Would you trust this prediction? (g) How many customers does your model predict will show up on day where the high temperature is 90° F? Would you trust this prediction? (h) Construct the residual plot for this data. Is a linear model appropriate? Why or why not?

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Question
Q1
Question 1) Suppose you are interested in studying the relationship between the temperature of a
particular day and the number of customers that a large ice cream shop serves on that day. To do
this you randomly choose 11 days to visit the shop and record both the high temperature of that
day and how many customers it served for the entire day. You get the following data:
High Temperature (in ° F)
75
83
92
77
92
86
73
96
85
88
80
Number of Customers
430
480
600
400
510
520
370
590
590
520
430
(a) Draw a scatterplot for this data. Make sure to label your axes.
(b) Calculate the correlation coefficient, and decide if there is enough evidence for a correlation.
(c) Construct the LSR for this data. Keep one decimal place for the slope and round the intercept
to the nearest whole number.
(d) Graph the LSR on your scatterplot.
(e) Write a sentence interpreting the slope of the LSR.
(f) How many customers does your model predict will show up on day where the high temperature
is 50° F? Would you trust this prediction?
(g) How many customers does your model predict will show up on day where the high temperature
is 90° F? Would you trust this prediction?
(h) Construct the residual plot for this data. Is a linear model appropriate? Why or why not?
Transcribed Image Text:Question 1) Suppose you are interested in studying the relationship between the temperature of a particular day and the number of customers that a large ice cream shop serves on that day. To do this you randomly choose 11 days to visit the shop and record both the high temperature of that day and how many customers it served for the entire day. You get the following data: High Temperature (in ° F) 75 83 92 77 92 86 73 96 85 88 80 Number of Customers 430 480 600 400 510 520 370 590 590 520 430 (a) Draw a scatterplot for this data. Make sure to label your axes. (b) Calculate the correlation coefficient, and decide if there is enough evidence for a correlation. (c) Construct the LSR for this data. Keep one decimal place for the slope and round the intercept to the nearest whole number. (d) Graph the LSR on your scatterplot. (e) Write a sentence interpreting the slope of the LSR. (f) How many customers does your model predict will show up on day where the high temperature is 50° F? Would you trust this prediction? (g) How many customers does your model predict will show up on day where the high temperature is 90° F? Would you trust this prediction? (h) Construct the residual plot for this data. Is a linear model appropriate? Why or why not?
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 9 steps with 33 images

Blurred answer
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman