Model 1 Coefficients Unstandardized Coefficients B Std. Error -386.390 .476 -158.827 .185 (Constant) Income Travelling Income Travelling a. Dependent Variable: Total spending 1282.583 .377 300.692 .085 Standardized Coefficients Beta .253 -.175 .882 t -.301 1.260 -.528 2.186 Sig. Explain how to interpret the finding that the interaction between income and the amount of travelling is positive (rather than negative). .766 .219 .602 .038
Model 1 Coefficients Unstandardized Coefficients B Std. Error -386.390 .476 -158.827 .185 (Constant) Income Travelling Income Travelling a. Dependent Variable: Total spending 1282.583 .377 300.692 .085 Standardized Coefficients Beta .253 -.175 .882 t -.301 1.260 -.528 2.186 Sig. Explain how to interpret the finding that the interaction between income and the amount of travelling is positive (rather than negative). .766 .219 .602 .038
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 10CYU
Related questions
Question
![f
What determines how much money a family spends on holiday? In a survey, a sample of 30 families
were asked to keep a record of their spending during a one-week holiday and report their total
spending at the end of the week. The researchers hypothesised that wealthier families tend to spend
more, and that families who tend to spend most of the time in one town tend to spend less than
those who travel around to see sight at several different places. Therefore, the respondents were
asked to report the net monthly income of the family as well as the number of different settlements
(villages, towns, and cities) that they visited during the week. A multiple linear regression model
revealed that both income and the amount of travelling are significantly related to total spending.
The researchers, however, also hypothesised that the two independent variables may interact. The
SPSS printout below indicates that there is evidence for an interaction (at a = .05), and therefore the
interaction model is a good fit to the data.
Model
1
Model
1
R
.922a
Model Summary
a. Predictors: (Constant), Income
Travelling
Regression
Residual
R Square
.850
Adjusted R
Square
.833
Sum of
Squares
63217471.22
11129918.65
74347389.87
Travelling, Income,
ANOVA
df
3
d=1196266
26
29
Std. Error of
the Estimate
654.273
Mean Square
21072490.41
428073.794
Total
a. Dependent Variable: Total spending
b. Predictors: (Constant), Income Travelling, Income, Travelling
F
49.226
Sig.
.000b
Рабочий сто](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F05fd0771-1903-468c-a296-b6ad4a4a7dd3%2F7d5fb449-1439-4e40-b9cc-fae72ebd04c7%2F7wrxt9i_processed.jpeg&w=3840&q=75)
Transcribed Image Text:f
What determines how much money a family spends on holiday? In a survey, a sample of 30 families
were asked to keep a record of their spending during a one-week holiday and report their total
spending at the end of the week. The researchers hypothesised that wealthier families tend to spend
more, and that families who tend to spend most of the time in one town tend to spend less than
those who travel around to see sight at several different places. Therefore, the respondents were
asked to report the net monthly income of the family as well as the number of different settlements
(villages, towns, and cities) that they visited during the week. A multiple linear regression model
revealed that both income and the amount of travelling are significantly related to total spending.
The researchers, however, also hypothesised that the two independent variables may interact. The
SPSS printout below indicates that there is evidence for an interaction (at a = .05), and therefore the
interaction model is a good fit to the data.
Model
1
Model
1
R
.922a
Model Summary
a. Predictors: (Constant), Income
Travelling
Regression
Residual
R Square
.850
Adjusted R
Square
.833
Sum of
Squares
63217471.22
11129918.65
74347389.87
Travelling, Income,
ANOVA
df
3
d=1196266
26
29
Std. Error of
the Estimate
654.273
Mean Square
21072490.41
428073.794
Total
a. Dependent Variable: Total spending
b. Predictors: (Constant), Income Travelling, Income, Travelling
F
49.226
Sig.
.000b
Рабочий сто
![Model
1
Unstandardized Coefficients
B
Std. Error
-386.390
.476
-158.827
.185
(Constant)
Income
Travelling
Income Travelling
a. Dependent Variable: Total spending
Coefficients
A▾ B I =
1282.583
.377
300.692
.085
Standardized
Coefficients
Beta
.253
-.175
.882
t
-.301
1.260
-.528
2.186
Sig.
Explain how to interpret the finding that the interaction between income and the amount of
travelling is positive (rather than negative).
.766
.219
.602
.038](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F05fd0771-1903-468c-a296-b6ad4a4a7dd3%2F7d5fb449-1439-4e40-b9cc-fae72ebd04c7%2Foc8dpbq_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Model
1
Unstandardized Coefficients
B
Std. Error
-386.390
.476
-158.827
.185
(Constant)
Income
Travelling
Income Travelling
a. Dependent Variable: Total spending
Coefficients
A▾ B I =
1282.583
.377
300.692
.085
Standardized
Coefficients
Beta
.253
-.175
.882
t
-.301
1.260
-.528
2.186
Sig.
Explain how to interpret the finding that the interaction between income and the amount of
travelling is positive (rather than negative).
.766
.219
.602
.038
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