- There is a significant difference in likelihood of having dinner based on education level (p=<0.001). - Bachelor's degree and higher education levels reported significantly lower likelihood than less than high school or high school graduate. - Master's degree and doctorate degree reported significantly lower likelihood than all other education levels. - No other significant differences were found between other education level groups.

1. Corey Wagner
BUAD302
2:00-3:15
Instructor: Suresh Sundaram

2. 1.
Queston
1. eatrest
2. totspent
3. watchtv
4. tvprogram
5. tvnewsviewer
6. newstime
7. surfnet
Measure
Nominal
Ratio
Nominal
Nominal
Nominal
Nominal
Nominal
central tendency
mode= 1
mean= $158.59
mode= 1
mode= 3
mode= 1
Measure of Variation
frquency distribution: yes 100%, no 0%
standard deviation = $90.78
frequency distribution: yes 95.8%, no 4.2%
standard deviation = .985
frquency distrubtion: yes 89.1%, no 10.9%
mode= 4
mode= 3
frequency distrbution: 7am News 9.1%, 6pm news 35.5.%, 10
pm news, 55.3%
frequency distribution: less than 1 hour 6.2% 1-2 hours
8. websitevisit
9. smartphone
10. location
11. distance
12. wine
13. chef
14. waitsatff
15. unique
16. local
17. attractive
18. music
19. parking
20. likely
21. avprice
Nominal
Nominal
interval
Interval
Interval
Interval
Interval
Interval
Interval
interval
Interval
Interval
Interval
Ratio
mode= 3
mode= 2
mean= 2.47
mean= 3.29
mean=3.54
mean= 3.59
mean= 3.54
mean= 3.60
mean= 2.43
mean=3.68
mean= 3.48
mean= 2.30
mean= 3
mean= $24.09
Frequncy distribution: News 13.9 %, Sports 16.9%, Shopping
30.3%, Social Media 14.5 %, Other 24.3
frequency distrubtion: yes 44.5%, no 55.5%
standard deviation = 1.35
standard deviation = 1.31
standard deviation = 1.50
standard deviation = 1.50
standard deviation = 1.47
standard deviation = 1.54
standard deviation = 1.48
standard deviation = 1.51
standard deviation = 1.41
standard deviation = 1.224
standard deviation = 1.226
standard deviation = 10.111
22. birthyear
Ratio
mean= 1967.52
standard deviation = 9.99
23. education
Nominal
mode= 6
24. maritalstatus Nominal
mode= 2
25. hometype
26. familysize
Nominal
Ratio
mode= 4
mean= 2.64
27. zipcode
Nominal
mode= 3
28. income
29. gender
30. Age
Nominal
Nominal
ratio
mode = 4
mode = 1
mean = 45.48
frequency distribution: less than high school 2.8%, some
high school 2.8%, high gradaduate 3.6%, some college (no
degree) 3.4%, associate degree 3.6%, bachelor's degree
59.9%, masters degree 21.6%, doctorate degree 2.2%
frequency distribution: single 24.4%, married 66.9%, other
8.7%
frequency distribution: rental apartmen 25.6%,
condominium 25.3%, townhome 21.2%, single family home
27.9%
standard deviation 1.382
frequency distribution: north 5%, east 27.9%, west 55.7%,
south 9.5%
frequency distribution: <$15,000 6.4%
$15,000 to $24,999 8.1%
$25,000 to $49,999 20.4%
$50,000 to $74,999 33.9%
$75,000 to $99,999 3.6
$100,000 to $149,999 10.1%
$150,000+ 17.4%
frequency distribution: male 52.7%, female 47.3%
standard deviation: 9.99

3. Changes that were made to the original data table
Variable number and
characteristic that was
adjusted
4: tvprogram
What scale it originally
was listed as:
What scale it was
changed to:
Why the variable scale
was changed:
Scale
Nominal
12: wine
Nominal
Interval
15: unique
Nominal
Interval
16: local
Nominal
Interval
19: parking
Nominal
Interval
22: birthyear
Nominal
Ratio
23: education
Ordinal
Ratio
It was changed form
scale to nominal
because this question
has to deal with
specific categorical
data that can be
grouped
It was changed from
nominal to interval
because there are
values for customers
to choose from that
are divided into
intervals
It was changed from
nominal to interval
because there are
values for customers
to choose from that
are divided into
intervals
It was changed from
nominal to interval
because there are
values for customers
to choose from that
are divided into
intervals
It was changed from
nominal to interval
because there are
values for customers
to choose from that
are divided into
intervals
Zero is a value that
could be provided as
an adequate response
Zero (no education) is
a value that could be
provided as an
adequate response

4. 2.
a)
Null hypothesis: Men and women spend the same amount of money, on a monthly basis, on
lunch or dinner at restaurants.
Alternative hypothesis: Men and women do not spend the same amount of money, on a
monthly basis, on lunch or dinner at restaurants.
Analysis: I ran an independent samples t-test for Chef Gaston in order to determine if Men and
women, which were the group variable, spend the same amount of money, on a monthly basis,
on lunch or dinner at restaurants. I reject the null hypothesis, and accept the alternative
hypothesis. The statistical significance level is .024, which is lower than .05, the confidence
interval level. Therefore, women spend more money then men, on average; women spend
$169.99 in comparison to men who only spend $148.34 per month.
Recommendation: Determine what is least appealing about restaurants to men, and improve
upon that aspect. Also, determine what the most liked quality of restaurants is and emphasize
that as a critical aspect of your restaurant, that will drive more male clientele to your
restaurant, thus equating the amount of money spent by males and females.

5. b)
Null hypothesis: The expected average price for an evening entrée item alone is the same for men and
women.
Alternative Hypothesis: The expected average price for an evening entrée item alone is not the same
for men and women.
Analysis: I ran an independent sample t-test in order to determine if men and women expected the
average price for an evening entrée item alone to differentiate between the two groups. The variable is
not statistically significant because the significant level of .230 is greater than the confidence level of .05
for the variable. Therefore, I would not reject the null hypothesis and assume that men and women
have an equivalent expected average price for an evening entrée item alone. Men have an average
expectation of their evening entrée item alone being $24.50 compared to women who believe theirs will
be $23.63.
Recommendation: Advertise to the community that price is consistent across the entree menu,
therefore demonstrating to patrons that your restaurant is more concerned with the quality of food
serviced rather than inflating prices on food items that are ordered most often by males or females
c)
Group Statistics
Would you describe yourself
N
Mean
Std. Deviation
Std. Error Mean
as one who watches
television?
Yes
342
3.65
1.516
.082
No
15
4.27
1.387
.358
Attractive Décor

6. Independent Samples Test
Levene's Test for
t-test for Equality of Means
Equality of Variances
F
Sig.
T
df
Sig. (2-
Mean
Std. Error
95% Confidence
tailed)
Differenc
Differenc
Interval of the
e
e
Difference
Lower
Equal variances
Attractive
.065
355
.126
-.612
.399
-1.395
.172
-
15.50
.116
-.612
.367
-1.393
.169
1.665
assumed
Décor
3.435
-
Upper
3
1.535
Equal variances
not assumed
Null hypothesis: People who watch television and those who don’t are the same in terms of the
importance attached to attractive décor.
Alternative Hypothesis: People who watch television and those who don’t are the different in
terms of the importance attached to attractive décor.
Analysis: For my analysis I ran an independent sample t-test. In doing so I was able to
determine that there was not a difference between to two sample means. After reviewing the
statistics, I would not reject the null hypothesis because the significance level is .065, which is
higher than the level of confidence of .05. Meaning that people who watch television and those
who don’t are the same in terms of the importance attached to attractive décor. Also, with the
F statistic being low,that demonstrates that there is not significant difference between the
groups, which reaffirms not rejecting the null hypothesis.
Recommendation: Decorate your restaurant with attractive décor because, whether the
person watches television or not, they view attractive décor as an important aspect of a
restaurant.
d)
Group Statistics
Would you describe yourself
N
Mean
Std. Deviation
Std. Error Mean
as one who watches
television?
Yes
342
2.30
1.209
.065
No
15
2.20
1.568
.405
Free Valet Parking
Independent Samples Test

7. Levene's Test for
t-test for Equality of Means
Equality of
Variances
F
Sig.
t
df
Sig. (2-
Mean
Std.
95% Confidence
tailed)
Differenc
Error
Interval of the
e
Differenc
Difference
e
Equal variances
Free Valet
.239
355
.748
.104
.323
-.531
.740
.254 14.74
Equal variances
.322
Upper
.803
.104
.410
-.771
.979
assumed
Parking
1.393
Lower
not assumed
0
Null hypothesis:People who watch television and those who don’t are the same in terms of the
importance attached to valet parking.
Alternative Hypothesis: People who watch television and those who don’t differ in terms of the
importance attached to valet parking.
Analysis: I would not reject the null hypothesis and state that: people who watch television and
those who don’t are the same in terms of the importance attached to valet parking. I ran an
independent samples t-test to evaluate the two samples,which gave me a significance level of
.239, which is higher than the confidence level of .05. The F statistics is small, 1.393, which
reaffirms that there is not significant differences between the groups, and that the independent
variable probably does not have a significant impact on the dependent variable.
Recommendation: Valet parking should be provided at your restaurant because people who
watch television and those who don’t are the same terms of how important they believe it is.
Therefore, when you are interviewing potential employees for the valet positions, make sure
they are quality drivers and have positive personalities to make the valet process as enjoyable
as possible for the individuals that patronize your restaurant and use the service.
3.
ANOVA

8. Based on the description of the restaurant you just saw, how likely are
you to have dinner at this restaurant?
Sum of
Df
Mean
F
Sig.
Squares
Square
Between
199.356
7
28.479 29.613
.000
Groups
Within Groups
335.642
349
.962
Total
534.997
356
Multiple Comparisons
Dependent Variable: Based on the description of the restaurant you just saw, how likely are
you to have dinner at this restaurant?
Scheffe
(I) What is your
(J) What is your
Mean
Std.
Sig.
95% Confidence
highest level of
highest level of
Difference Error
Interval
education you
education you
(I-J)
Lower
Upper
have achieved?
have achieved?
Bound
Bound
Some High School
.300
.439 1.000
-1.36
1.96
High School
.092
.412 1.000
-1.46
1.65
Graduate
Some College (No
Degree)
Associate Degree
Bachelor's Degree
Master's Degree
Doctorate Degree
Less than High
School
High School
Graduate
Some College (No
Some High School
Degree)
Associate Degree
Bachelor's Degree
Master's Degree
Doctorate Degree
Less than High
High School
School
Graduate
Some High School
Less than High
School
.317
.420
.999
-1.27
1.90
-.831
-1.796*
-2.055*
-3.350*
-.300
.412
.317
.330
.465
.439
.773
.000
.000
.000
1.000
-2.39
-2.99
-3.30
-5.11
-1.96
.73
-.60
-.81
-1.59
1.36
-.208
.412
1.000
-1.76
1.35
.017
.420
1.000
-1.57
1.60
-1.131
-2.096*
-2.355*
-3.650*
-.092
.412
.317
.330
.465
.412
.380
.000
.000
.000
1.000
-2.69
-3.29
-3.60
-5.41
-1.65
.43
-.90
-1.11
-1.89
1.46
.208
.412
1.000
-1.35
1.76

9. Some College (No
Degree)
Associate Degree
Bachelor's Degree
Master's Degree
Doctorate Degree
Less than High
School
Some High School
High School
Some College (No
Graduate
Degree)
Associate Degree
Bachelor's Degree
Master's Degree
Doctorate Degree
Less than High
School
Some High School
High School
Graduate
Associate Degree
Some College (No
Degree)
Bachelor's Degree
Master's Degree
Doctorate Degree
Less than High
School
Some High School
High School
Graduate
Bachelor's Degree
Some College (No
Degree)
Associate Degree
Master's Degree
Doctorate Degree
Less than High
School
Some High School
Master's Degree
High School
Graduate
Some College (No
Degree)
.224
.393
1.000
-1.26
1.71
-.923
-1.889*
-2.147*
-3.442*
-.317
.385
.280
.294
.441
.420
.569
.000
.000
.000
.999
-2.38
-2.95
-3.26
-5.11
-1.90
.53
-.83
-1.04
-1.78
1.27
-.017
-.224
.420
.393
1.000
1.000
-1.60
-1.71
1.57
1.26
-1.147
-2.113*
-2.371*
-3.667*
.831
.393
.291
.304
.448
.412
.291
.000
.000
.000
.773
-2.63
-3.21
-3.52
-5.36
-.73
.33
-1.01
-1.22
-1.98
2.39
1.131
.923
.412
.385
.380
.569
-.43
-.53
2.69
2.38
1.147
.393
.291
-.33
2.63
-.965
-1.224*
-2.519*
1.796*
.280
.294
.441
.317
.109
.017
.000
.000
-2.02
-2.33
-4.18
.60
.09
-.11
-.86
2.99
2.096*
1.889*
.317
.280
.000
.000
.90
.83
3.29
2.95
2.113*
.291
.000
1.01
3.21
.965
-.258
-1.554*
2.055*
.280
.130
.353
.330
.109
.787
.008
.000
-.09
-.75
-2.89
.81
2.02
.23
-.22
3.30
2.355*
2.147*
.330
.294
.000
.000
1.11
1.04
3.60
3.26
2.371*
.304
.000
1.22
3.52

10. 1.224*
.258
-1.295
3.350*
.294
.130
.364
.465
.017
.787
.085
.000
.11
-.23
-2.67
1.59
2.33
.75
.08
5.11
3.650*
3.442*
.465
.441
.000
.000
1.89
1.78
5.41
5.11
3.667*
.448
.000
1.98
5.36
2.519*
.441
.000
.86
4.18
Bachelor's Degree
Master's Degree
Doctorate Degree
Associate Degree
Bachelor's Degree
Doctorate Degree
Less than High
School
Some High School
High School
Graduate
Some College (No
Degree)
Associate Degree
*
.353
.364
.008
.085
.22
-.08
2.89
2.67
1.554
1.295
*. The mean difference is significant at the 0.05 level.
Based on the description of the restaurant you just
saw, how likely are you to have dinner at this
restaurant?
a,b
Scheffe
What is your highest
N
Subset for alpha = 0.05
level of education
1
2
3
you have achieved?
Some College (No
12
1.08
Degree)
Some High School
10
1.10
High School
13
1.31
Graduate
Less than High
10
1.40
School
Associate Degree
13
2.23
2.23
Bachelor's Degree
214
3.20
Master's Degree
77
3.45
3.45
Doctorate Degree
8
4.75
Sig.
.226
.154
.103
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 13.797.
b. The group sizes are unequal. The harmonic mean of the
group sizes is used. Type I error levels are not guaranteed.

11. Null hypothesis: The differences in the likelihood to patronize are not likely to exist between all
groups of customers based on education level
Alternative hypothesis:The differences in the likelihood to patronize are likely to exist between
all groups of customers based on education level
Analysis: The N column indicates that 10 individuals have an education level of less than high
school, 10 individuals have some high school education,13 individuals are high school
graduates, 12 individuals have some college education but no degree, 13 individuals have
associate degrees, 214 individuals have bachelor degrees, 77 individuals have masterdegrees,
and 8 individuals have doctorate degrees. Thus, the highest numbers of individuals with a
particular education are those with bachelor degrees. The question is, however, is whether
customers who are more educated are more likely to patronize the new restaurant? Looking at
the numbers in the mean column, we see that the likelihood of returning is lower for individuals
with lower education. That is, the numbers in the numbers in the Mean column indicate that
individuals with a doctorate degree report a likelihood of returning of 4.75.Thus, the likelihood
of returning to the new restaurant means become larger with the more education an individual
receives.
Looking at the information in the table from the Scheff test, the significance column
shows that differences between some of the group means are statistically significant (.000,
.008, and .017) while others are not (1.000, .999, .773, .380, .569, .291, .109, .787). More
specifically, the means of the doctorate degree, masters degree and bachelors degree are
statistically significant. In contrast, individuals with some high school education, high school
graduates, individuals with some high school education but no degree, and associate degrees
are not statistically significant. Thus, the means of individuals with doctorate degree, masters
degree and bachelors degree are statistically different from those individuals with some high
school education, high school graduates, and individuals with some high school education but
no degree. The means of individuals with an Associates degree is statistically significant when
being compared only to Masters degrees and Doctorate degrees. Also, when comparing the
mean for Bachelors degree to Doctorate degree is statistically significant. In conclusion, we can
state that customers education levels does influence the likelihood of returning, but the
influence is not significant until a customer has an education level of a bachelors degree or
higher.
I would reject the null hypothesis and conclude that, in fact, there truly are differences
in the means of likelihood of returning based on the level of education received.
Recommendations:I would createan advertisingfor Chef Gaston that was geared toward
individuals with lower education. By creating some sort of incentive program for individuals
with lower income, it would help to increase the likelihood of returning. Also, do further
research as to why these individuals with lower income are not returning as much in order to
provide the most accurate and efficient advertising campaign possible.
4.

12. One-Sample Statistics
N Mean
Std.
Deviatio
n
Wine Selection
63 1.33
.475
Famous Chef
63 1.46
.502
Locally-sourced
63 4.52
.503
Ingredients
Live Music
63 1.63
.485
t
Wine Selection
Famous Chef
Locally-sourced
Ingredients
Live Music
Std.
Error
Mean
.060
.063
.063
.061
One-Sample Test
Test Value = 5
df
Sig. (2Mean
tailed) Differenc
e
-61.245
-55.919
-7.508
62
62
62
.000
.000
.000
-3.667
-3.540
-.476
-55.035
62
.000
-3.365
95% Confidence
Interval of the
Difference
Lower
Upper
-3.79
-3.55
-3.67
-3.41
-.60
-.35
-3.49
-3.24
Null hypothesis: Potential Patrons that are “Completely likely” will definitely not think that the
Wine selection, Famous Chef, Locally sourced ingredients, and live music are “completely
important” to patronize Chef Gaston’s restaurant.
Alternative hypothesis: Potential Patrons that are “Completely likely” will definitely think that
the Wine selection, Famous Chef, Locally sourced ingredients, and live music are “completely
important” to patronize Chef Gaston’s restaurant.
Analysis: I conducted a one-sample t-test to determine if potential patrons who are
“completely likely” to patronize Chef Gaston’s restaurant consider Wine selection, Famous
Chef, Locally sourced ingredients, and live music characteristics that are “completely
important”. According to the means that were derived from the test, Wine selection had a
mean of 1.33, which fell between completely unimportant and somewhat unimportant. Having
a famous chef for a restaurant had a mean of 1.46, which fell in between completely
unimportant and somewhat unimportant. Locally sourced ingredients received a mean 4.52,
which falls in between somewhat important and completely important. Lastly, live music
received a mean score of 1.63, which is between completely unimportant and somewhat
unimportant. In conclusion, I would reject the null hypothesis because all the variables have a

13. statistical significance level of .000. We can conclude that potential patronsthat are
“completely likely” will definitely think that the Wine selection, Famous Chef, Locally sourced
ingredients, and live music are “completely important” to patronize Chef Gaston’s restaurant.
Recommendation: Throughout the advertising campaign for Chef Gaston’s restaurant, make
sure to emphasize the fact that the restaurant has a wine selection, Famous Chef, Locally
sourced ingredients, and live music. People believe that are likely to visit the restaurant believe
these are completely important so therefore it is crucial to notify these individuals that these
amenities are provided at Chef Gaston’s restaurant.
5.
Between-Subjects Factors
Value Label
1
<$15,000
$15,000 to
2
$24,999
$25,000 to
3
Which of the
$49,999
following categories
$50,000 to
best describes your 4
$74,999
before tax household
$75,000 to
income?
5
$99,999
$100,000 to
6
$149,999
7
$150,000+
1
Sports
What types of
2
Comedy
programs do you
watch most on
3
Drama
television?
4
Talk Shows
N
19
27
71
116
13
35
61
56
67
146
73
Tests of Between-Subjects Effects
Dependent Variable: Based on the description of the restaurant you just saw,
how likely are you to have dinner at this restaurant?
Source
Type III Sum
df
Mean
F
Sig.
of Squares
Square
a
Corrected Model
390.151
19
20.534
57.820
.000
Intercept
1102.996
1
1102.996 3105.801
.000
income
94.496
6
15.749
44.347
.000

14. tvprogram
19.311
3
6.437
income *
12.215
10
1.221
tvprogram
Error
114.355
322
.355
Total
3661.000
342
Corrected Total
504.506
341
a. R Squared = .773 (Adjusted R Squared = .760)
18.125
3.439
.000
.000
Descriptive Statistics
Dependent Variable: Based on the description of the restaurant you just saw,
how likely are you to have dinner at this restaurant?
Which of the following
categories best
describes your before
tax household
income?
What types of
programs do you
watch most on
television?
Sports
Total
Sports
$15,000 to $24,999
Total
Comedy
Drama
$25,000 to $49,999
Talk Shows
Total
Comedy
Drama
$50,000 to $74,999
Talk Shows
Total
Sports
Comedy
$75,000 to $99,999
Drama
Talk Shows
Total
Sports
Comedy
$100,000 to $149,999 Drama
Talk Shows
Total
Sports
$150,000+
Comedy
<$15,000
Mean
1.32
1.32
1.11
1.11
3.00
2.64
2.91
2.70
2.83
2.72
2.82
2.75
2.00
4.00
3.00
4.33
3.85
4.50
4.60
2.00
4.75
4.57
3.29
4.44
Std.
Deviation
.671
.671
.424
.424
.000
.485
.302
.460
.408
.452
.670
.509
.
1.155
.000
.816
1.068
.707
.754
.
.452
.778
.951
.948
N
19
19
27
27
5
55
11
71
6
82
28
116
1
4
2
6
13
2
20
1
12
35
7
32

15. Total
Drama
Talk Shows
Total
Sports
Comedy
Drama
Talk Shows
Total
3.83
4.69
4.31
1.59
4.21
2.73
3.68
3.04
.408
.479
.904
1.075
1.008
.516
1.066
1.216
6
16
61
56
67
146
73
342
Pairwise Comparisons
Dependent Variable: Based on the description of the restaurant you just saw, how likely are
you to have dinner at this restaurant?
(I) Which of the
(J) Which of the
Mean
Std.
Sig.d
95% Confidence
following
following
Difference Error
Interval for Differenced
categories best
categories best
(I-J)
Lower
Upper
describes your
describes your
Bound
Bound
before tax
before tax
household
household
income?
income?
$15,000 to
.205a,b
.178
.252
-.146
.556
$24,999
$25,000 to
-1.533a,b,*
.176
.000
-1.878
-1.187
$49,999
$50,000 to
-1.476a,b,*
.165
.000
-1.800
-1.151
$74,999
<$15,000
$75,000 to
-2.018a,*
.247
.000
-2.504
-1.531
$99,999
$100,000 to
-2.647a,*
.234
.000
-3.108
-2.186
$149,999
$150,000+
-2.745a,*
.166
.000
-3.072
-2.418
a,b
<$15,000
-.205
.178
.252
-.556
.146
a,b,*
$25,000 to
-1.737
.159
.000
-2.051
-1.424
$49,999
$50,000 to
-1.680a,b,*
.147
.000
-1.970
-1.391
$15,000 to
$74,999
$24,999
$75,000 to
-2.222a,*
.236
.000
-2.687
-1.758
$99,999
$100,000 to
-2.851a,*
.222
.000
-3.289
-2.414
$149,999

16. $25,000 to
$49,999
$50,000 to
$74,999
$75,000 to
$99,999
$100,000 to
$149,999
$150,000+
$150,000+
<$15,000
$15,000 to
$24,999
$50,000 to
$74,999
$75,000 to
$99,999
$100,000 to
$149,999
$150,000+
<$15,000
$15,000 to
$24,999
$25,000 to
$49,999
$75,000 to
$99,999
$100,000 to
$149,999
$150,000+
<$15,000
$15,000 to
$24,999
$25,000 to
$49,999
$50,000 to
$74,999
$100,000 to
$149,999
$150,000+
<$15,000
$15,000 to
$24,999
$25,000 to
$49,999
$50,000 to
$74,999
$75,000 to
$99,999
$150,000+
<$15,000
-2.950a,*
1.533a,b,*
1.737a,b,*
.149
.176
.159
.000
.000
.000
-3.242
1.187
1.424
-2.657
1.878
2.051
.057a,b
.144
.692
-.226
.340
-.485a,*
.234
.039
-.945
-.025
-1.114a,*
.220
.000
-1.547
-.681
-1.213a,*
1.476a,b,*
1.680a,b,*
.145
.165
.147
.000
.000
.000
-1.499
1.151
1.391
-.926
1.800
1.970
-.057a,b
.144
.692
-.340
.226
-.542a,*
.226
.017
-.986
-.098
-1.171a,*
.211
.000
-1.587
-.755
-1.270a,*
2.018b,*
2.222b,*
.132
.247
.236
.000
.000
.000
-1.529
1.531
1.758
-1.010
2.504
2.687
.485b,*
.234
.039
.025
.945
.542b,*
.226
.017
.098
.986
-.629*
.281
.026
-1.181
-.077
-.728*
2.647b,*
2.851b,*
.227
.234
.222
.001
.000
.000
-1.174
2.186
2.414
-.281
3.108
3.289
1.114b,*
.220
.000
.681
1.547
1.171b,*
.211
.000
.755
1.587
.629*
.281
.026
.077
1.181
-.099
2.745b,*
.213
.166
.643
.000
-.517
2.418
.320
3.072

17. $15,000 to
2.950b,*
.149
.000
2.657
$24,999
$25,000 to
1.213b,*
.145
.000
.926
$49,999
$50,000 to
1.270b,*
.132
.000
1.010
$74,999
$75,000 to
.728*
.227
.001
.281
$99,999
$100,000 to
.099
.213
.643
-.320
$149,999
Based on estimated marginal means
*. The mean difference is significant at the
a. An estimate of the modified population marginal mean (I).
b. An estimate of the modified population marginal mean (J).
d. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no
adjustments).
3.242
1.499
1.529
1.174
.517
Estimates
Dependent Variable: Based on the description of the restaurant you
just saw, how likely are you to have dinner at this restaurant?
What types of
programs do you
watch most on
television?
Sports
Comedy
Drama
Talk Shows
Mean
2.443a
3.774a
2.838a
3.900a
Std.
Error
95% Confidence Interval
Lower
Upper
Bound
Bound
.157
.100
.155
.079
2.134
3.578
2.532
3.745
2.751
3.970
3.143
4.056
a. Based on modified population marginal mean.
Pairwise Comparisons
Dependent Variable: Based on the description of the restaurant you just saw, how likely are
you to have dinner at this restaurant?
(I) What types of
(J) What types of
Mean
Std.
Sig.d
95% Confidence
programs do you
programs do you
Difference Error
Interval for Differenced

18. watch most on
television?
watch most on
(I-J)
Lower
Upper
television?
Bound
Bound
Comedy
-1.332*,b,c
.186
.000
-1.697
-.966
b,c
Sports
Drama
-.395
.221
.074
-.830
.039
Talk Shows
-1.458*,b,c
.176
.000
-1.803
-1.112
*,b,c
Sports
1.332
.186
.000
.966
1.697
*,b,c
Comedy
Drama
.936
.184
.000
.573
1.299
b,c
Talk Shows
-.126
.127
.322
-.376
.124
b,c
Sports
.395
.221
.074
-.039
.830
*,b,c
Drama
Comedy
-.936
.184
.000
-1.299
-.573
*,b,c
Talk Shows
-1.062
.174
.000
-1.405
-.720
*,b,c
Sports
1.458
.176
.000
1.112
1.803
b,c
Talk Shows
Comedy
.126
.127
.322
-.124
.376
*,b,c
Drama
1.062
.174
.000
.720
1.405
Based on estimated marginal means
*. The mean difference is significant at the
b. An estimate of the modified population marginal mean (I).
c. An estimate of the modified population marginal mean (J).
d. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no
adjustments).
4. Which of the following categories best describes your before tax household income?
* What types of programs do you watch most on television?
Dependent Variable: Based on the description of the restaurant you just saw, how likely are
you to have dinner at this restaurant?
Which of the following What types of
Mean
Std.
95% Confidence Interval
categories best
programs do you
Error
Lower
Upper
describes your before watch most on
Bound
Bound
tax household
television?
income?
<$15,000
$15,000 to $24,999
$25,000 to $49,999
Sports
Comedy
Drama
Talk Shows
Sports
Comedy
Drama
Talk Shows
Sports
1.316
.a
.a
.a
1.111
.a
.a
.a
.a
.137
.
.
.
.115
.
.
.
.
1.047
.
.
.
.885
.
.
.
.
1.585
.
.
.
1.337
.
.
.
.

19. Comedy
3.000
.267
2.476
Drama
2.636
.080
2.478
Talk Shows
2.909
.180
2.556
a
Sports
.
.
.
Comedy
2.833
.243
2.355
$50,000 to $74,999
Drama
2.720
.066
2.590
Talk Shows
2.821
.113
2.600
Sports
2.000
.596
.828
Comedy
4.000
.298
3.414
$75,000 to $99,999
Drama
3.000
.421
2.171
Talk Shows
4.333
.243
3.855
Sports
4.500
.421
3.671
Comedy
4.600
.133
4.338
$100,000 to $149,999
Drama
2.000
.596
.828
Talk Shows
4.750
.172
4.412
Sports
3.286
.225
2.843
Comedy
4.438
.105
4.230
$150,000+
Drama
3.833
.243
3.355
Talk Shows
4.688
.149
4.394
a. This level combination of factors is not observed, thus the corresponding population
marginal mean is not estimable.
Null hypothesis:There will be no difference between the mean ratings for likelihood to have
dinner at Chef Gaston’s new restaurant for customers that watch different types of television
programs and there will also be no difference between customers who have different before
tax household income.
Alternative hypothesis: There will be a difference between the mean ratings for likelihood to
have dinner at Chef Gaston’s new restaurant for customers that watch different types of
television programs and there will also be a difference between customers who have different
before tax household income.
Analysis: The test of between-subject effects table shows that the F-ratio for income is 44.347,
which is statistically significant at the .000 level. This means that customers who eat at Chef
Gaston’s restaurant with different before tax household income vary in the likelihood of
recommending the restaurant. The F-ratio of for type of television programs the consumers
watch is 18.125, which is also statistically significant at the .000 level. This means that the type
of television programs the consumer watches influences the likelihood of recommending the
restaurant. The means in the descriptive statistics table show that the average likelihood of
recommending Chef Gaston’s restaurant increases with a higher household before tax income.
Thus, customers who have a before tax household income of $150,000+ and $100,000$149,999 show an average likelihood to recommend of 4.31 and 4.57, compared to $75,000-
3.524
2.794
3.263
.
3.312
2.849
3.043
3.172
4.586
3.829
4.812
5.329
4.862
3.172
5.088
3.729
4.645
4.312
4.981

20. $99,999 (3.85), $74,999-$50,000 (2.75), $49,999-$25,000 (2.70), $24,999-$15,000 (1.1), and
less than $15,000 (1.32).
Chef Gaston was also interested in whether there was a difference in the likelihood to
patronize the restaurant is influenced by type of television programs the consumers watch.
The F-ratio for tvprograms is large 18.125 and statistically important (.000). This means that
customers will be significantly more likely to recommend the restaurant to others depending on
what television program they watch. There are two groups that are more likely to recommend,
talk shows and comedy with an average likelihood to recommend of 3.9 and 3.774, compared
to 2.838 and 2.443 respectively.
The interaction between before tax household income and type of television programs
the consumers watch has an F-ratio of 3.439 and is statistically significant at .000. This means
that there is interaction between before tax household income,type of television programs the
consumers watch, and likelihood of recommending Chef Gaston’s restaurant. Lastly, 77.3
percent of the variation in before tax household income is accounted for by type of television
programs the consumers watch in the likelihood to recommend Chef Gaston’s restaurant is
associated with satisfaction.
Recommendation:Advertise Chef Gaston’s new restaurant on talk show and comedy television
programs and in areas where the most amount of individuals live with $100,000-$149,999, and
plus $150,000 before tax household income live. This will help to maximize the best target
customers for the new restaurant.
6)
a)
Group Statistics
What is your gender?
Based on the description of
N
Male
Std. Deviation
Std. Error Mean
188
3.07
1.263
.092
169
the restaurant you just saw,
how likely are you to have
Mean
2.93
1.183
.091
Female
dinner at this restaurant?
Independent Samples Test
Levene's Test for
t-test for Equality of Means
Equality of
Variances
F
Sig.
t
df
Sig. (2-
Mean
Std.
95% Confidence
tailed)
Differenc
Error
Interval of the
e
Differenc
Difference
e
Lower
Upper

21. Based on the
Equal variances
description of
1.474
.225 1.079
assumed
.281
.140
.130
-.115
.396
1.083 354.3
the restaurant
355
.280
.140
.129
-.114
.395
you just saw,
80
how likely are
Equal variances
you to have
not assumed
dinner at this
restaurant?
Null hypothesis: There is no difference in appeal for Chef Gaston’s restaurant for men or
women
Alternative hypothesis: :There is a difference in appeal for Chef Gaston’s restaurant for men or
women
Analysis: The amount of male customers was 188 and the amount of female customers in Chef
Gaston’s data set was 169. The mean satisfaction level for males was 3.07, which was a bit
higher compared to that of the females, 2.93. The standard deviation for females is somewhat
smaller, 1.183, than for the males, 1.263. The statistical significance level is .225 and is greater
than .05; therefore we fail to reject the null hypothesis.
Recommendations: The advertising campaign that will be created for the restaurant should be
gender neutral to appeal to both men and women.
b)
ANOVA
Based on the description of the restaurant you just saw, how likely are you to have dinner at
this restaurant?
Sum of Squares
df
Mean Square
Between Groups
253.542
3
84.514
Within Groups
250.964
338
504.506
113.824
Sig.
.742
Total
F
.000
341
Multiple Comparisons
Dependent Variable: Based on the description of the restaurant you just saw, how likely are you to have dinner at this
restaurant?
Scheffe
(I) What types of
(J) What types of
programs do you watch
programs do you watch
most on television?
most on television?
Mean
Difference (IJ)
Std. Error
Sig.
95% Confidence Interval
Lower Bound
Upper Bound

22. -2.620
*
.156
.000
-3.06
-2.18
Drama
-1.144
*
.135
.000
-1.52
-.76
Talk Shows
-2.096
*
.153
.000
-2.53
-1.67
2.620
*
.156
.000
2.18
3.06
1.476
*
.127
.000
1.12
1.83
.524
*
.146
.005
.11
.93
1.144
*
.135
.000
.76
1.52
-1.476
*
.127
.000
-1.83
-1.12
-.952
*
.124
.000
-1.30
-.61
2.096
*
.153
.000
1.67
2.53
-.524
*
.146
.005
-.93
-.11
.952
*
.124
.000
.61
1.30
Comedy
Sports
Sports
Comedy
Drama
Talk Shows
Sports
Drama
Comedy
Talk Shows
Sports
Talk Shows
Comedy
Drama
*. The mean difference is significant at the 0.05 level.
Based on the description of the restaurant you just saw, how likely are you to have
dinner at this restaurant?
Scheffe
a,b
What types of programs do
N
Subset for alpha = 0.05
you watch most on
1
2
3
4
television?
Sports
56
Drama
146
Talk Shows
2.73
73
Comedy
1.59
67
Sig.
3.68
4.21
1.000
1.000
1.000
1.000
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 75.004.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error
levels are not guaranteed.
Null hypothesis: The appeals for Chef Gaston’s restaurant does not differ by the type of
programs that respondents watch most on television.
Alternative hypothesis: The appeals for Chef Gaston’s restaurant does differ by the type of
programs respondents watch most on television.
Analysis:A one-way analysis of variance was the statistical test that was the most appropriate.
By analyzing the significance level of .000, it shows that the variable (type of programs they
watch on television) is statistically significant, so we conclude that we would reject the null
hypothesis. We assume that the appeals of Chef Gaston’s restaurant do differ by the type of
programs respondents watch most on television. Analyzing the F-ratio, it has a value of

23. 113.824, which is large. That means that there is significant differences between the groups
and that the independent variable, type of programs they watch on television, influences the
dependent variable, the likelihood to have dinner at Chef Gaston’s restaurant. Individuals who
watch comedy are the most likely to have dinner at Chef Gaston’s restaurant, with an mean of
4.21, followed by talk shows with a mean of 3.68, then dramas with a mean of 2.73, and lastly
those who watch sports are the least likely, with a mean of 1.59, to have dinner at Chef
Gaston’s restaurant. Lastly, the Sheffe test results show that certain means fall outside the
range of the confidence interval, thus reaffirming the need to reject the null hypothesis and
conclude that the pairs of means are statistically different.
Recommendations: Focus most of your advertising on comedy and talk show programs on
television. These are were you will be able to reach the widest audience of consumers that will
also be the most likely to come eat at Chef Gaston’s restaurant.
c)
ANOVA
Based on the description of the restaurant you just saw, how likely are you to have dinner at
this restaurant?
Sum of Squares
Between Groups
df
Mean Square
4.033
5
.807
Within Groups
530.964
351
534.997
Sig.
1.513
Total
F
.533
.751
356
Null hypothesis:The appeals for Chef Gaston’s restaurant does not differ by the number of
hours that respondents spend surfing the internet on an average day.
Alternative hypothesis:The appeals for Chef Gaston’s restaurant does differ by the number of
hours that respondents spend surfing the internet on an average day.
Analysis:There is no statistical difference between the groups. Therefore, the number of hours
that respondents spend surfing the Internet on an average day does not have an impact on the
appeals of Chef Gaston’s restaurant. The F-ratio is small, .533, which determine that there is no
statistical difference between the groups.
Recommendation:Advertising dollars should not be spent trying to market Chef Gaston’s
restaurant on the Internet because patrons are going to the come to the restaurant regardless of
the hours they spend on the internet.

24. d)
ANOVA
Based on the description of the restaurant you just saw, how likely are you to have dinner at
this restaurant?
Sum of Squares
df
Mean Square
Between Groups
187.758
4
46.940
Within Groups
326.242
332
514.000
47.768
Sig.
.983
Total
F
.000
336
Multiple Comparisons
Dependent Variable: Based on the description of the restaurant you just saw, how likely are
you to have dinner at this restaurant?
Scheffe
(I) What type of website (J) What type of website
Mean
Std.
Sig. 95% Confidence
do you spend the most
do you spend the most
Differe Error
Interval
time on, when you are
time on, when you are
nce (ILower Upper
surfing the Internet?
surfing the Internet?
J)
Bound Bound
Sports (ESPN.com,
-.368
.195 .471
-.97
.24
NFL.com, etc.)
Shopping (Amazon.com,
.918*
.175 .000
.38
1.46
News (CNN.com,
Buy.com, etc.)
FoxNews.com, etc.)
Social Media (Facebook,
2.090*
.202 .000
1.46
2.72
Twitter, etc.)
Other
.751*
.181 .002
.19
1.31
News (CNN.com,
.368
.195 .471
-.24
.97
FoxNews.com, etc.)
Shopping (Amazon.com,
1.286*
.164 .000
.78
1.79
Sports (ESPN.com,
Buy.com, etc.)
NFL.com, etc.)
Social Media (Facebook,
2.458*
.193 .000
1.86
3.06
Twitter, etc.)
Other
1.119*
.171 .000
.59
1.65
*
News (CNN.com,
-.918
.175 .000
-1.46
-.38
FoxNews.com, etc.)
Sports (ESPN.com,
-1.286*
.164 .000
-1.79
-.78
Shopping (Amazon.com,
NFL.com, etc.)
Buy.com, etc.)
Social Media (Facebook,
1.172*
.172 .000
.64
1.71
Twitter, etc.)
Other
-.167
.147 .863
-.62
.29

25. News (CNN.com,
FoxNews.com, etc.)
Sports (ESPN.com,
Social Media (Facebook,
NFL.com, etc.)
Twitter, etc.)
Shopping (Amazon.com,
Buy.com, etc.)
Other
News (CNN.com,
FoxNews.com, etc.)
Sports (ESPN.com,
NFL.com, etc.)
Other
Shopping (Amazon.com,
Buy.com, etc.)
Social Media (Facebook,
Twitter, etc.)
*. The mean difference is significant at the 0.05 level.
-2.090*
.202 .000
-2.72
-1.46
-2.458*
.193 .000
-3.06
-1.86
-1.172*
.172 .000
-1.71
-.64
-1.339*
-.751*
.179 .000
.181 .002
-1.89
-1.31
-.78
-.19
-1.119*
.171 .000
-1.65
-.59
.167
.147 .863
-.29
.62
1.339*
.179 .000
.78
1.89

26. Based on the description of the restaurant you just
saw, how likely are you to have dinner at this
restaurant?
a,b
Scheffe
What type of website do you
N
Subset for alpha =
spend the most time on,
0.05
when you are surfing the
1
2
3
Internet?
Social Media (Facebook,
49 1.61
Twitter, etc.)
Shopping (Amazon.com,
102
2.78
Buy.com, etc.)
Other
82
2.95
News (CNN.com,
47
3.70
FoxNews.com, etc.)
Sports (ESPN.com,
57
4.07
NFL.com, etc.)
Sig.
1.000 .928 .376
Means for groups in homogeneous subsets are displayed.
a. Uses Harmonic Mean Sample Size = 61.555.
b. The group sizes are unequal. The harmonic mean of the
group sizes is used. Type I error levels are not guaranteed.
Null hypothesis: The appeals for Chef Gaston’s restaurant does not differ by the type of website
they spend the most time on, when surfing the internet.
Alternative hypothesis: The appeals for Chef Gaston’s restaurant does differ by the type of
website they spend the most time on, when surfing the internet.
Analysis: The means for the type of websites that consumers spend the most time on, when they
are surfing the internet are: Social media (1.61), Shopping (2.78), Other (2.95), News (3.70), and
sports (4.07). With a large F-ratio of 47.768, it is statistically significant at .000. Looking at the
information in the significance column we see that differences between some of the group means
are statistically significant (.000) while others are not (.471). Specifically, the means of the News
and Sports (.471) as well as Shopping and Other (.863) are not statistically significantly. As a
general conclusion, we can state that the type of website a consumer they spend the most time
on, when they are surfing the Internet does influence the appeal of Chef Gaston’s restaurant. We
would reject the null hypothesis and accept the alternative hypothesis.
Recommendations: Advertise more on sports and news websites because they have the highest
average of being likely to have dinner at Chef Gaston’s restaurant.

27. 7)
a)
Paired Samples Statistics
Mean
N
Std. Deviation
Std. Error Mean
Upscale Location
357
1.351
.071
Located with 30 minutes
3.29
357
1.313
.069
Famous Chef
3.59
357
1.501
.079
Knowledgeable Wait Staff
3.54
357
1.470
.078
Unique Menu
3.60
357
1.543
.082
Locally-sourced Ingredients
2.43
357
1.484
.079
Wine Selection
3.54
357
1.501
.079
Free Valet Parking
Pair 1
2.57
2.30
357
1.224
.065
driving distance
Pair 2
Pair 3
Pair 4
Paired Samples Correlations
N
Upscale Location & Located
Pair 1
Correlation
Sig.
357
-.807
.000
357
.817
.000
357
-.884
.000
357
-.531
.000
with 30 minutes driving
distance
Pair 2
Pair 3
Pair 4
Famous Chef &
Knowledgeable Wait Staff
Unique Menu & Locallysourced Ingredients
Wine Selection & Free Valet
Parking
Paired Samples Test
Paired Differences
Mean
t
Std.
Std. Error
95% Confidence Interval
Deviation
Mean
of the Difference
Lower
Upper
df
Sig. (2tailed)

28. Upscale Location Pair
2.532
.134
-.983
-.456
-5.372
356
.000
.059
.899
.048
-.035
.152
1.236
356
.217
1.165
2.938
.156
.859
1.471
7.494
356
.000
1.244
2.388
.126
.995
1.492
9.841
356
.000
Located with 30
1
-.720
minutes driving
distance
Pair
2
Pair
3
Famous Chef Knowledgeable Wait
Staff
Unique Menu Locally-sourced
Ingredients
Pair
Wine Selection -
4
Free Valet Parking
Null hypothesis: Customers are more likely to patronize a restaurant at an upscale location or
located within 30 minutes driving distance.
Alternative hypothesis:Customers are not more likely to patronize a restaurant at an upscale
location or located within 30 minutes driving distance.
Analysis:Running a paired samples t-test, I was able to come up with the means for unique
food, 2.57, and for located within 30 minutes driving distance, the mean is 3.29. The t-value for
this comparison is -5.372 and it is significant at the .000 level. Thus we can reject the null
hypothesis that the two means are equal. Moreover, we can conclude that patrons have
somewhat more favorable perceptions of a restaurant being located within 30 minutes driving
distance than unique food.
Recommendations:Advertise to consumers in a 30 minute driving distance radius of the
restaurant because that variable is an important aspect of whether they are the most likely to
patronize Chef Gaston’s restaurant.
b)
Null hypothesis: Customers are more likely to patronize a restaurant with a famous chef or one
that has knowledgeable wait staff.
Alternative hypothesis: Customers are not more likely to patronize a restaurant with a famous
chef or one that has knowledgeable wait staff.
Analysis:Running a paired sample t-test, I was able to come up with the means for having a
famous chef, 3.59, and for a knowledgeable wait staff, 3.54. The t-value for this comparison is
1.236 and it is not significant because of the level of .217. Thus, we do not reject the null

29. hypothesis that the two means are equal. Moreover, we can conclude that patrons have the
same perception of a restaurant with a famous chef and one that has a knowledgeable staff.
Recommendations:Advertise to potential patrons of Chef Gaston’s new restaurant that he is a
famous chef and that the wait staff is knowledgeable, because these two variables had a
reasonably high mean value for appeal to the restaurant if these characteristics existed.
c)
Null hypothesis: Customers are more likely to patronize a restaurant with a unique menu or
one that sources with ingredients locally.
Alternative hypothesis: Customers are more likely to patronize a restaurant with a unique
menu or one that sources with ingredients locally.
Analysis:Running a paired sample t-test, I was able to come up with the means for a unique
menu, 3.60, and for locally sourced ingredients is 2.43. The t-value for this comparison is 7.494
and it is significant at the .000 level. Thus we can reject the null hypothesis that the two means
are equal. Moreover, we can conclude that patrons have somewhat more favorable
perceptions of a restaurant with a unique menu than one with locally sourced ingredients.
Recommendations:Advertise to potential patrons that Chef Gaston’s new restaurant has a
unique menu because customers are more likely to patronize the restaurant for that variable
more than a restaurant that sources their ingredients locally.
d)
Null hypothesis: Customers are more likely to patronize a restaurant that has a better wine
selection or one that offers free valet parking.
Alternative hypothesis: Customers are more likely to patronize a restaurant that has a better
wine selection or one that offers free valet parking.
Analysis:Running a paired sample t-test, I was able to come up with the means for wine
selection, 3.54, and for free valet parking, 2.30. The t-value for this comparison is 9.841 and it is
significant at the .000 level. Thus we can reject the null hypothesis that the two means are
equal. Moreover, we can conclude that patrons have somewhat more favorable perceptions of
a restaurant with a wine selection than one with free valet parking.

30. Recommendations:Advertise to potential patrons that Chef Gaston’s new restaurant has a
better wine selection because customers believe that offering free valet is not statistically
significant enough for them to be more likely to patronize the restaurant.
8)
a)
On average, on a
monthly basis, how
much do you spend
on lunch or dinner at
restaurants?
One-Sample Statistics
N
Mean
Std.
Deviation
357 $158.5910
$90.78166
Std. Error
Mean
$4.80467
One-Sample Test
t
On average, on a
monthly basis, how
much do you spend
on lunch or dinner at
restaurants?
1.788
Df
356
Test Value = 150
Sig. (2Mean
95% Confidence Interval
tailed)
Difference
of the Difference
Lower
Upper
.075
$8.59104
-$0.8581
$18.0402
Null hypothesis: the mean of X2 - on average on a monthly basis, how much do you spend on
lunch or dinner at restaurants - will not be significantly different from $150.
Alternative hypothesis: the mean of the answers to X2 - on average on a monthly basis, how
much do you spend on lunch or dinner at restaurants - will not be $150.
Analysis:The top table is labeled one-sample Statistics and shows the mean, standard deviation,
and standard error for X2 - on average on a monthly basis, how much do you spend on lunch or
dinner at restaurants – (a mean of $158.59 and a standard deviation of $90.78). The one
sample test table below shows the results of the t-test for the null hypothesis that the average

31. response to X2 is $150 (test value of 150). The test statistic is 1.788, and the significance level is
.075. This means that the null hypothesis cannot be rejected. The results indicate respondents
spend about what Chef Gaston believed they do,on average, per month in restaurants for meals
only.
Recommendation:Chef Gaston can conclude that customers spend about $150 per month in
restaurants for meals only. More research should be done to determine what would be an
average price of a meal should be that would be on Chef Gaston’s menu, this would maximize
the amount of people that come into his restaurant.
b)
What would you
expect an average
evening meal entree
item alone to be
priced?
One-Sample Statistics
N
Mean
Std.
Deviation
305 $24.0951
$10.11126
t
What would you
expect an average
evening meal entree
item alone to be
priced?
7.073
Std. Error
Mean
$0.57897
One-Sample Test
Test Value = 20
Df
Sig. (2Mean
tailed)
Difference
304
.000
95% Confidence Interval
of the Difference
Lower
Upper
$4.09508
$2.9558
$5.2344
Null hypothesis: the mean of the X21 – what would you expect an average evening meal entrée
item alone to be priced?- will not be significantly different from $20.
Alternative hypothesis: the means of the answers to X21 – what would you expect an average
evening meal entrée item alone to be priced? - will not be $20.
Analysis:The top table is labeled one-sample Statistics and shows the mean, standard deviation,
and standard error for X21 -what would you expect an average evening meal entrée item alone

32. to be priced?– (a mean of $29.09 and a standard deviation of $10.11). The one sample test
table below shows the results of the t-test for the null hypothesis that the average response to
X21 is $20 (test value of 20). The test statistic is 7.073, and the significance level is .000. This
means that the null hypothesis can be rejected and the alternative hypothesis accepted with a
high level of confidence from a statistical perspective. The results indicate respondents expect
to be paying higher than what Chef Gaston believed to pay for an evening meal entrée.
Recommendation: Advertise to potential patrons that they can expect to pay less than their
current expectation for an evening meal entrée since his estimate for what an evening meal
entrée was $20 while patrons actually expect to pay $29.09.
c)
One-Sample Statistics
N
How many people
live in your home
(include all children
under 18 living with
you)?
357
t
How many people
live in your home
(include all children
under 18 living with
you)?
-18.571
Mean
2.64
Std.
Deviation
1.382
Std. Error
Mean
.073
One-Sample Test
Test Value = 4
df
Sig. (2Mean
tailed)
Difference
356
.000
95% Confidence Interval
of the Difference
Lower
Upper
-1.359
-1.50
-1.21
Null hypothesis: the mean of the X26 – how many people live in your home (include all children
under 18 living with you)- will not be significantly different form 4.
Alternative hypothesis: the mean of the answers to X26 – how many people live in your home
(include all children under 18 living with you)- will not be 4.

33. Analysis:The top table is labeled one-sample Statistics and shows the mean, standard deviation,
and standard error for X26 -– how many people live in your home (include all children under 18
living with you)– (a mean of $2.64 and a standard deviation of $1.382). The one sample test
table below shows the results of the t-test for the null hypothesis that the average response to
X26 is 4 (test value = 4). The test statistic is -18.57, and the significance level is .000. This means
that the null hypothesis can be rejected and the alternative hypothesis accepted with a high
level of confidence from a statistical perspective. The results indicate respondents have less
people living in their home than what Chef Gaston believed.
Recommendation:Advertise to small families because the mean response for variable X 26 - how
many people live in your home (include all children under 18 living with you)- was 2.64, which is
statistically different from the estimate of four that Chef Gaston gave.
d)
Calculated Age of
Respondent
One-Sample Statistics
N
Mean
Std.
Deviation
357 45.4846
9.99342
Std. Error
Mean
.52891
One-Sample Test
t
Calculated Age of
Respondent
.916
df
356
Test Value = 45
Sig. (2Mean
tailed)
Difference
.360
95% Confidence Interval
of the Difference
Lower
Upper
.48459
-.5556
1.5248
Null hypothesis: the mean of the X30 – age of respondent- will not be significantly from 45.
Alternative hypothesis: the mean of the X30 – age of respondent- will not be 45.
Analysis:The top table is labeled one-sample Statistics and shows the mean, standard deviation,
and standard error for X26 –age of respondent– (a mean of 45.48 and a standard deviation of
9.993). The one sample test table below shows the results of the t-test for the null hypothesis
that the average response to X30 is 45 (test value = 45). The test statistic is .916, and the
significance level is .360. This means that the null hypothesis cannot be rejected. The results
indicate respondents have a similar calculated age as Chef Gaston’s target customers.

34. Recommendation: Chef Gaston’s estimate that the average age of his customers is 45 years
old. Therefore, advertise to potential patrons that maintain that average as their age in order to
reach Chef Gaston’s target customers.
9)
Mode
l
R
Model Summary
R
Adjusted R Std. Error of
Square
Square
the
Estimate
1
.807a
.651
.641
.735
a. Predictors: (Constant), Free Valet Parking,
Knowledgeable Wait Staff, Live Music, Located with
30 minutes driving distance, Upscale Location,
Locally-sourced Ingredients, Wine Selection, Unique
Menu, Famous Chef, Attractive Decor
Model
Sum of
Squares
ANOVAa
df
Mean
Square
F
Sig.
Regressio
348.071
10
34.807 64.428
.000b
n
1
Residual
186.926
346
.540
Total
534.997
356
a. Dependent Variable: Based on the description of the restaurant you just
saw, how likely are you to have dinner at this restaurant?
b. Predictors: (Constant), Free Valet Parking, Knowledgeable Wait Staff,
Live Music, Located with 30 minutes driving distance, Upscale Location,
Locally-sourced Ingredients, Wine Selection, Unique Menu, Famous Chef,
Attractive Decor
Model
1
(Constant)
Upscale Location
Coefficientsa
Unstandardized
Standardized
Coefficients
Coefficients
B
Std. Error
Beta
4.940
.568
-.169
.063
-.186
t
8.703
-2.664
Sig.
.000
.008

35. Located with 30
minutes driving
distance
Wine Selection
Famous Chef
Knowledgeable Wait
Staff
Unique Menu
Locally-sourced
Ingredients
Attractive Decor
-.027
.062
-.029
-.439
.661
-.290
-.092
.227
.075
.070
.059
-.356
-.113
.273
-3.868
-1.307
3.854
.000
.192
.000
-.153
.297
.065
.072
-.193
.359
-2.352
4.133
.019
.000
-.147
.075
-.182
-1.961
.051
Live Music
-.062
.062
-.071
-.992
.322
Free Valet Parking
-.117
.043
-.117
-2.733
.007
a. Dependent Variable: Based on the description of the restaurant you just saw, how likely
are you to have dinner at this restaurant?
Null hypothesis:There is no relationship between the ten variables (X10 – X19) and X20 - the
likelihood to patronize the restaurant- for Chef Gaston’s new restaurant.
Alternative hypothesis: The ten variables (X10 – X19) are significantly related to X20 - the
likelihood to patronize the restaurant.
Analysis:a multiple linear regression analysis was the SPSS statistical test that was conducted
for this question. The model summary table shows that the r-square for this model is .651. This
means that 65.1 percent of the variation in satisfaction (likelihood to patronize the restaurant)
can be explained by the ten independent variables (X10 – X19). The regression model results in
the ANOVA table indicate that the r-square for the overall model is significantly different from
zero (F-ratio = 64.428; significance level = .000). This probability means there are .000 chances
the regression model results come from a population where the R-Square actually is zero. That
is, there are no chances out of 1,000 that the actual correlation coefficient is zero.
To determine if one or more of the restaurant features are significant predictors of
satisfaction we examine the information provided in the Coefficients table. Looking at the
Standardized Coefficients Beta column reveals that location (beta = -.186, Sig. = .008), Wine
Selection (beta = -.356, Sig. = .000), Knowledgeable Wait Staff (beta = .273, Sig. = .000), Unique
Menu (beta = -.193, Sig. = .019), Locally sourced ingredients (beta = .359, Sig. = .000), and free
valet parking (beta = -.117, Sig. = .007) are all statistically significant. While, located within 30
minutes driving distance (beta = -.439, Sig. = .661), famous chef (beta = -1.307, Sig. =.192),
attractive décor (beta = -1.961, Sig. =.051), and live music (beta =-.992, Sig. = .332) are not
statistically significant. This means we can reject the null hypothesis that none of the restaurant
variables are related to the likelihood to patronize Chef Gaston’s restaurant. Thus, this

36. regression analysis tells us consumer perceptions of features about Chef Gaston’s restaurant,
for six of the restaurant variables, are good predictors of the likelihood to patronize the
restaurant.
Recommendations:Be cautious in interpreting these regression results. Location (-.186), wine
selection (-.365), unique menu (-.193), and free valet parking (-.117) all have negative beta
coefficients, which means these restaurant features haveless favorable perceptions that are
associated with higher levels of satisfaction. Therefore more research needs to be done as to
why results have occurred.