Solve question (b) please Critical Values for Correlation Coefficient0.9974 0.9505 0.8780.8117 0.7540.7079 0.66610 0.63211 0.60212 0.57613 0.55314 0.53215 0.51416 0.49717 0.48218 0.46819 0.45620 0.44421 0.43322 0.42323 0.41324 0.40425 0.39626 0.38827 0.38128 0.37429 0.36730 0.36139.8. An engineer wanted to determine how the weight of a car affects gas mileage.The following data represent the weight of various cars and their gas mileage.Complete parts (a) through (d).(a) Determine which variable is the likely explanatory variable and which is thelikely response variable.Weight Miles per oGallonThe explanatory variable is the miles per gallon and the response variableis the weight.Car (pounds)31803310398525803340The explanatory variable is the weight and the response variable is themiles per gallon.A23B19C18(b) Draw a scatter diagram of the data. Choose the correct scatter plot.2721OA.O B.E Click the icon to view the critical values table.304000Q15-2500Weight (Ibs)2500-15400030mpgC.OD.400030-250015152500Weight (Ibs)4000 LmpgWeight (Ibs)

Name: Solve question (b) please Critical Values for Correlation Coefficient0
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Description: Solve question (b) please Critical Values for Correlation Coefficient0.9974 0.9505 0.8780.8117 0.7540.7079 0.66610 0.63211 0.60212 0.57613 0.55314 0.53215 0.51416 0.49717 0.48218 0.46819 0.45620 0.44421 0.43322 0.42323 0.41324 0.40425 0.39626 0.38827

explanatory variable= x axis response variable = y axis Scatter plot:

Math

Statistics

An engineer wanted to determine how the weight of a car affects gas mileage. The following data represent the weight of various cars and their gas mileage. Complete parts (a) through (d). likely response variable. The explanatory variable is the miles per gallon and the response variable is the weight. Weight Car (pounds) 3180 3310 3985 2580 3340 Miles per o Gallon 23 The explanatory variable is the weight and the response variable is the miles per gallon. 19 18 27 C (b) Draw a scatter diagram of the data. Choose the correct scatter plot. 21 O B. Click the icon to view the critical values table. 40004 30- 15 2500 Weight (Ibs) 2500 15 4000 30 mpg C. OD. 4000 30 2500 15 15 30 2500 4000 L mpg Weight (Ibs) Weight (Ibs)

An engineer wanted to determine how the weight of a car affects gas mileage. The following data represent the weight of various cars and their gas mileage. Complete parts (a) through (d). likely response variable. The explanatory variable is the miles per gallon and the response variable is the weight. Weight Car (pounds) 3180 3310 3985 2580 3340 Miles per o Gallon 23 The explanatory variable is the weight and the response variable is the miles per gallon. 19 18 27 C (b) Draw a scatter diagram of the data. Choose the correct scatter plot. 21 O B. Click the icon to view the critical values table. 40004 30- 15 2500 Weight (Ibs) 2500 15 4000 30 mpg C. OD. 4000 30 2500 15 15 30 2500 4000 L mpg Weight (Ibs) Weight (Ibs)

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 23PPS

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Concept explainers

Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.

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Question

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Solve question (b) please

Critical Values for Correlation Coefficient
0.997
4 0.950
5 0.878
0.811
7 0.754
0.707
9 0.666
10 0.632
11 0.602
12 0.576
13 0.553
14 0.532
15 0.514
16 0.497
17 0.482
18 0.468
19 0.456
20 0.444
21 0.433
22 0.423
23 0.413
24 0.404
25 0.396
26 0.388
27 0.381
28 0.374
29 0.367
30 0.361
3
9.
8.

An engineer wanted to determine how the weight of a car affects gas mileage.
The following data represent the weight of various cars and their gas mileage.
Complete parts (a) through (d).
(a) Determine which variable is the likely explanatory variable and which is the
likely response variable.
Weight Miles per o
Gallon
The explanatory variable is the miles per gallon and the response variable
is the weight.
Car (pounds)
3180
3310
3985
2580
3340
The explanatory variable is the weight and the response variable is the
miles per gallon.
A
23
B
19
C
18
(b) Draw a scatter diagram of the data. Choose the correct scatter plot.
27
21
OA.
O B.
E Click the icon to view the critical values table.
30
4000
Q
15-
2500
Weight (Ibs)
2500-
15
4000
30
mpg
C.
OD.
4000
30-
2500
15
15
2500
Weight (Ibs)
4000 L
mpg
Weight (Ibs)

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