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r studio代写-EARN 5

时间：2021-03-05

NOTE: YOU CAN EARN 5 POINTS FOR EACH QUESTION, TOGETHER IN TOTAL MAXIMALLY 20

POINTS

QUESTION 1

A marketing agency explores how emotions affect the way people view commercials. For “Dove care

for men”, they created a commercial in which a young man uses the shampoo of his girlfriend. Due to

this shampoo effect, he grows shiny, long hair. The commercial ends with the advice to men to never

use their girlfriend's shampoo but to buy Dove shampoo for men. The agency wants to test whether

the attitude towards the commercial translates in higher purchase intention for men compared to

women.

1a. Formulate the main hypothesis in this research.

1b. Present this model graphically.

1c. What is the mathematical model to test this model?

QUESTION 2

2a. A telecom provider wants to know which Android smartphone sells best. To learn more about the

needs and interest of their customers, they design a survey. (i) Would you use comparative or non-

comparative survey questions? (ii) Give one advantage and one disadvantage of your choice.

2b. Name (i) two types of comparative scales and (ii) two types of non-comparative scales that are

available to a marketer.

2c. The telecom provider has a customer base of 15.000 people in the Netherlands. They want to draw

a representative sample. (i) What sampling method would you advise them, and why? (ii) Describe the

sampling process.

2d. One of the main motives for the survey is to find out how much customers are willing to pay for a

specific Android phone Galaxy S6 Edge. The price in the population is 250$, which you take as the true

population value. You would like to get an estimate that lies within a 10$ of the true population value

with 95% confidence. The standard deviation in the population is 80$. Calculate the sample size (see

formula sheet at the end of the exam).

QUESTION 3

Oxyme was approached by Philips to learn more about the customer's perception of their product

Respironics. Respironics is a mask that you can place on your face which is connected to an oxygen

machine. Oxyme collected all webtexts in which Respironics was mentioned. They tagged the texts in

which a mask is named by 1, and others by 0. Additionally, Oxyme coded all texts on the reported

sentiment which is either negative (-1), neutral (0) or positive (1). Below you find the cross table.

Mask * Sentiment Crosstabulation

Sentiment Total

-1,00 ,00 1,00

Mask

0

Count 130 197 127 454

Expected Count 141,7 172,1 140,2 454,0

% within Mask 28,6% 43,4% 28,0% 100,0%

1

Count 52 24 53 129

Expected Count 40,3 48,9 39,8 129,0

% within Mask 40,3% 18,6% 41,1% 100,0%

Total

Count 182 221 180 583

Expected Count 182,0 221,0 180,0 583,0

% within Mask 31,2% 37,9% 30,9% 100,0%

3a. The chisquare value is 26,263 with 2 degrees of freedom. Which hypothesis is tested by the

chisquare test on this table?

3b. Use the table provided to assess whether this hypothesis should be rejected or not at 95%

confidence interval.

3c. In the online texts, is the mask more often discussed as a) positive, b) negative, c)neutral, or a

combination of a,b, and c?

QUESTION 4

A luxurious clothing company wants to know whether people buy the new expensive clothes to

compensate negative feelings in their live, to uphold social status, or to derive hedonic pleasure. They

designed an online survey to be held among their customers. The customer list includes age, gender

and how long the customer is subscribed to their newsletter.

4a. (i) Would you choose proportionate stratified or systematic sampling? (ii) Describe one advantage

and (iii) one disadvantage for each sampling approach in this case.

4b. The survey included the compulsive buying scale (1 to 6), and the hedonic consumption scale (7 to

12). Interpret the output below. Discuss discriminant and convergent validity.

Pattern Matrix

a

Factor

1 2 3

1. If I have any money left at the end of the pay period, I just

have to spend it.

,824 ,261

2. I felt others would be horrified if they knew of my spending

habits.

,786 ,149

3. I bought things even though I couldn’t afford them. ,353 ,512

4. I wrote a check when I know I didn’t have enough money in the

bank to cover it.

,733

5. I felt anxious or nervous on days I didn’t go shopping. ,795

6. I feel driven to shop and spend, even when I don’t have the

time or the money.

,555 ,322

7. I like to shop for the novelty of it. ,742

8. Shopping satisfies my sense of curiosity. ,642

9. I feel like I’m exploring new worlds when I shop. ,858

10. Shopping offers new experience. ,604

11. I go shopping to watch other people. ,721

12. I go shopping to be entertained. ,431

Factor Correlation Matrix

Factor 1 2 3

1 1,000 -,262 ,215

2 -,262 1,000 -,182

3 ,215 -,182 1,000

4c. The company compares customers who score high on compulsive buying (labeled 1) and those who

score low (labeled 2). (i) Calculate the t-value and (ii) interpret the group differences in the table

below. Use the formula sheet provided at the end of the exam.

Group Statistics

Hedonic

Shopping

N Mean Std. Deviation Std. Error Mean

Purchase intention

1 103 1,46 ,872 ,086

2 101 1,18 ,518 ,052

QUESTION 5

Company GreenBuzz has a sustainable product they want to market in both Japan and the US. They

collect survey data among the customers in these countries about the motivations for environmental

behavior. In the data analysis, they regress environmental behavior (EB) on willingness to pay (WTP)

and environmental concern (EC). Below you can find their results. Note that the variable country is a

nominal variable, 0 identifies the US, and 1 Japan. EC stands for environmental concern and EB for

environmental behavior, both measured at a 5-point likert scale.

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 ,372

a

,139 ,137 ,80082586

ANOVA

a

Model Sum of Squares df Mean Square F Sig.

1 Regression 208,106 3 69,369 108,165 ,000

b

Residual 1292,905 2016 ,641

Total 1501,011 2019

Coefficients

a

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) -,256 ,024 -10,466 ,000

EC ,318 ,025 ,351 12,603 ,000

Country -,511 ,037 -,292 -13,836 ,000

EC*Country ,142 ,038 ,101 3,693 ,000

Dependent Variable: EB

5a. Which hypothesis is tested by the F values in the output?

5b. GreenBuzz expects that environmental concern (EC) more strongly translates into behavior (EB) in

Japan than in the US as Japan scores higher on collectivism. In collectivist countries, people are more

willing to do something for the greater good than in individualist countries. Are they correct, based on

the output above? Give argumentation based on your interpretation of the coefficients.

QUESTION 6

In the following analysis, the intention to go eating out in restaurants is explained by past behavior of

eating out in restaurants, optimistic feelings on the financial situation of their household, gender (male

are reference group), and a moderation effect of gender and past eating out behavior (eat_gender).

Both intention and past behavior are measured on a 7 point Likert scale ranging from ‘much less so’(1)

to ‘much more so’(7). Optimism is measured on a 7 point scale ranging from ‘not at all’(1) to

‘exceptionally’(7). For the question formulation see table 'descriptive statistics' below.

6a. Interpret the parameters, the fit of the model, and significance levels.

6b. Regression analysis can also be used to predict behavior, attitudes or purchase intentions. What

purchase intention scores does this model predict for a female person who is exceptionally optimistic

(score 7 on optimism) and is used to eating out in restaurants in the past six months (score 5 on past

behavior)?

6c. Below you can find the scatter plot of the standardized residuals and the predicted values. Based

on this scatter plot, do you think some assumptions of linear regression have been violated? Which

one(s)?

QUESTION 7

A travel agency wants to know the psychological benefits of holidays. Based on a survey held among

customers, they expect people who pursue happiness are more likely to go on holidays which will, in

turn, lead to lower levels of loneliness. The output of this analysis is shown below.

shortPI = intention to purchase short holidays

purhapp = pursuit of happiness

lonely = loneliness

**************************************************************************

Model

Y = lonely

X = purhapp

M = shortPI

Sample size

2458

**************************************************************************

Outcome: shortPI

Model Summary

R R-sq MSE F df1 df2 p

,1556 ,0242 ,9802 60,9152 1,0000 2456,0000 ,0000

Model

coeff se t p LLCI ULCI

constant ,0302 ,0200 1,5087 ,1315 -,0091 ,0694

purhapp -,1723 ,0221 -7,8048 ,0000 -,2156 -,1290

**************************************************************************

Outcome: lonely

Model Summary

R R-sq MSE F df1 df2 p

,2428 ,0589 ,7436 76,8930 2,0000 2455,0000 ,0000

Model

coeff se t p LLCI ULCI

constant -,0158 ,0174 -,9037 ,3662 -,0500 ,0184

shortPI ,1228 ,0176 6,9848 ,0000 ,0883 ,1572

purhapp -,1759 ,0195 -9,0355 ,0000 -,2140 -,1377

******************** DIRECT AND INDIRECT EFFECTS *************************

Direct effect of X on Y

Effect SE t p LLCI ULCI

-,1759 ,0195 -9,0355 ,0000 -,2140 -,1377

Indirect effect of X on Y

Effect Boot SE BootLLCI BootULCI

shortPI -,0212 ,0042 -,0309 -,0140

**************************************************************************

7a. Draw the conceptual model that is estimated below. Place the coefficients next to the arrows in

the model.

7b. Calculate the indirect effect that is noted in the output above, and discuss whether this is

significant based on a 95% confidence interval.

Formula sheet

2 2

2

z

n

D

,

/

X

t

s n

,

1

c

nN

n

N n

, 1 2

2 2

1 1 2 2/ /

X X

t

s n s n

,

2

2

(1 )z

n

D

,

(1 )

1

p

N n

n N

,

X

n

,

(1 )

p

p p

S

n

,

2 2

2

C z

n

R

, D R ,

X

X

z

,

1X

N n

Nn

, D R , 1

/

D

n

D

D

t

s n

, 1 2 1 2

2 2

1 1 2 2

( ) ( )

/ /

X X

t

n n

, 1 2 1 2

2 2

1 1 2 2

( ) ( )

/ /

X X

t

s n s n

2n

2

i 1

(obs exp )

exp

i i

i

X

, 2 ( 1) ( 1)Xdf c r ,

/

/

regression regression

residual residual

SSE df

F ratio

SSE df

,

2 explained

total

SSE

R

SSE

critical z-value 95% confidence interval (two-tailed) is 1.96

critical z-value 99% confidence interval (two-tailed) is 2.58

critical z-value 95% confidence interval (one-tailed) is 1.65

critical z-value 99% confidence interval (one-tailed) is 2.33

POINTS

QUESTION 1

A marketing agency explores how emotions affect the way people view commercials. For “Dove care

for men”, they created a commercial in which a young man uses the shampoo of his girlfriend. Due to

this shampoo effect, he grows shiny, long hair. The commercial ends with the advice to men to never

use their girlfriend's shampoo but to buy Dove shampoo for men. The agency wants to test whether

the attitude towards the commercial translates in higher purchase intention for men compared to

women.

1a. Formulate the main hypothesis in this research.

1b. Present this model graphically.

1c. What is the mathematical model to test this model?

QUESTION 2

2a. A telecom provider wants to know which Android smartphone sells best. To learn more about the

needs and interest of their customers, they design a survey. (i) Would you use comparative or non-

comparative survey questions? (ii) Give one advantage and one disadvantage of your choice.

2b. Name (i) two types of comparative scales and (ii) two types of non-comparative scales that are

available to a marketer.

2c. The telecom provider has a customer base of 15.000 people in the Netherlands. They want to draw

a representative sample. (i) What sampling method would you advise them, and why? (ii) Describe the

sampling process.

2d. One of the main motives for the survey is to find out how much customers are willing to pay for a

specific Android phone Galaxy S6 Edge. The price in the population is 250$, which you take as the true

population value. You would like to get an estimate that lies within a 10$ of the true population value

with 95% confidence. The standard deviation in the population is 80$. Calculate the sample size (see

formula sheet at the end of the exam).

QUESTION 3

Oxyme was approached by Philips to learn more about the customer's perception of their product

Respironics. Respironics is a mask that you can place on your face which is connected to an oxygen

machine. Oxyme collected all webtexts in which Respironics was mentioned. They tagged the texts in

which a mask is named by 1, and others by 0. Additionally, Oxyme coded all texts on the reported

sentiment which is either negative (-1), neutral (0) or positive (1). Below you find the cross table.

Mask * Sentiment Crosstabulation

Sentiment Total

-1,00 ,00 1,00

Mask

0

Count 130 197 127 454

Expected Count 141,7 172,1 140,2 454,0

% within Mask 28,6% 43,4% 28,0% 100,0%

1

Count 52 24 53 129

Expected Count 40,3 48,9 39,8 129,0

% within Mask 40,3% 18,6% 41,1% 100,0%

Total

Count 182 221 180 583

Expected Count 182,0 221,0 180,0 583,0

% within Mask 31,2% 37,9% 30,9% 100,0%

3a. The chisquare value is 26,263 with 2 degrees of freedom. Which hypothesis is tested by the

chisquare test on this table?

3b. Use the table provided to assess whether this hypothesis should be rejected or not at 95%

confidence interval.

3c. In the online texts, is the mask more often discussed as a) positive, b) negative, c)neutral, or a

combination of a,b, and c?

QUESTION 4

A luxurious clothing company wants to know whether people buy the new expensive clothes to

compensate negative feelings in their live, to uphold social status, or to derive hedonic pleasure. They

designed an online survey to be held among their customers. The customer list includes age, gender

and how long the customer is subscribed to their newsletter.

4a. (i) Would you choose proportionate stratified or systematic sampling? (ii) Describe one advantage

and (iii) one disadvantage for each sampling approach in this case.

4b. The survey included the compulsive buying scale (1 to 6), and the hedonic consumption scale (7 to

12). Interpret the output below. Discuss discriminant and convergent validity.

Pattern Matrix

a

Factor

1 2 3

1. If I have any money left at the end of the pay period, I just

have to spend it.

,824 ,261

2. I felt others would be horrified if they knew of my spending

habits.

,786 ,149

3. I bought things even though I couldn’t afford them. ,353 ,512

4. I wrote a check when I know I didn’t have enough money in the

bank to cover it.

,733

5. I felt anxious or nervous on days I didn’t go shopping. ,795

6. I feel driven to shop and spend, even when I don’t have the

time or the money.

,555 ,322

7. I like to shop for the novelty of it. ,742

8. Shopping satisfies my sense of curiosity. ,642

9. I feel like I’m exploring new worlds when I shop. ,858

10. Shopping offers new experience. ,604

11. I go shopping to watch other people. ,721

12. I go shopping to be entertained. ,431

Factor Correlation Matrix

Factor 1 2 3

1 1,000 -,262 ,215

2 -,262 1,000 -,182

3 ,215 -,182 1,000

4c. The company compares customers who score high on compulsive buying (labeled 1) and those who

score low (labeled 2). (i) Calculate the t-value and (ii) interpret the group differences in the table

below. Use the formula sheet provided at the end of the exam.

Group Statistics

Hedonic

Shopping

N Mean Std. Deviation Std. Error Mean

Purchase intention

1 103 1,46 ,872 ,086

2 101 1,18 ,518 ,052

QUESTION 5

Company GreenBuzz has a sustainable product they want to market in both Japan and the US. They

collect survey data among the customers in these countries about the motivations for environmental

behavior. In the data analysis, they regress environmental behavior (EB) on willingness to pay (WTP)

and environmental concern (EC). Below you can find their results. Note that the variable country is a

nominal variable, 0 identifies the US, and 1 Japan. EC stands for environmental concern and EB for

environmental behavior, both measured at a 5-point likert scale.

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 ,372

a

,139 ,137 ,80082586

ANOVA

a

Model Sum of Squares df Mean Square F Sig.

1 Regression 208,106 3 69,369 108,165 ,000

b

Residual 1292,905 2016 ,641

Total 1501,011 2019

Coefficients

a

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) -,256 ,024 -10,466 ,000

EC ,318 ,025 ,351 12,603 ,000

Country -,511 ,037 -,292 -13,836 ,000

EC*Country ,142 ,038 ,101 3,693 ,000

Dependent Variable: EB

5a. Which hypothesis is tested by the F values in the output?

5b. GreenBuzz expects that environmental concern (EC) more strongly translates into behavior (EB) in

Japan than in the US as Japan scores higher on collectivism. In collectivist countries, people are more

willing to do something for the greater good than in individualist countries. Are they correct, based on

the output above? Give argumentation based on your interpretation of the coefficients.

QUESTION 6

In the following analysis, the intention to go eating out in restaurants is explained by past behavior of

eating out in restaurants, optimistic feelings on the financial situation of their household, gender (male

are reference group), and a moderation effect of gender and past eating out behavior (eat_gender).

Both intention and past behavior are measured on a 7 point Likert scale ranging from ‘much less so’(1)

to ‘much more so’(7). Optimism is measured on a 7 point scale ranging from ‘not at all’(1) to

‘exceptionally’(7). For the question formulation see table 'descriptive statistics' below.

6a. Interpret the parameters, the fit of the model, and significance levels.

6b. Regression analysis can also be used to predict behavior, attitudes or purchase intentions. What

purchase intention scores does this model predict for a female person who is exceptionally optimistic

(score 7 on optimism) and is used to eating out in restaurants in the past six months (score 5 on past

behavior)?

6c. Below you can find the scatter plot of the standardized residuals and the predicted values. Based

on this scatter plot, do you think some assumptions of linear regression have been violated? Which

one(s)?

QUESTION 7

A travel agency wants to know the psychological benefits of holidays. Based on a survey held among

customers, they expect people who pursue happiness are more likely to go on holidays which will, in

turn, lead to lower levels of loneliness. The output of this analysis is shown below.

shortPI = intention to purchase short holidays

purhapp = pursuit of happiness

lonely = loneliness

**************************************************************************

Model

Y = lonely

X = purhapp

M = shortPI

Sample size

2458

**************************************************************************

Outcome: shortPI

Model Summary

R R-sq MSE F df1 df2 p

,1556 ,0242 ,9802 60,9152 1,0000 2456,0000 ,0000

Model

coeff se t p LLCI ULCI

constant ,0302 ,0200 1,5087 ,1315 -,0091 ,0694

purhapp -,1723 ,0221 -7,8048 ,0000 -,2156 -,1290

**************************************************************************

Outcome: lonely

Model Summary

R R-sq MSE F df1 df2 p

,2428 ,0589 ,7436 76,8930 2,0000 2455,0000 ,0000

Model

coeff se t p LLCI ULCI

constant -,0158 ,0174 -,9037 ,3662 -,0500 ,0184

shortPI ,1228 ,0176 6,9848 ,0000 ,0883 ,1572

purhapp -,1759 ,0195 -9,0355 ,0000 -,2140 -,1377

******************** DIRECT AND INDIRECT EFFECTS *************************

Direct effect of X on Y

Effect SE t p LLCI ULCI

-,1759 ,0195 -9,0355 ,0000 -,2140 -,1377

Indirect effect of X on Y

Effect Boot SE BootLLCI BootULCI

shortPI -,0212 ,0042 -,0309 -,0140

**************************************************************************

7a. Draw the conceptual model that is estimated below. Place the coefficients next to the arrows in

the model.

7b. Calculate the indirect effect that is noted in the output above, and discuss whether this is

significant based on a 95% confidence interval.

Formula sheet

2 2

2

z

n

D

,

/

X

t

s n

,

1

c

nN

n

N n

, 1 2

2 2

1 1 2 2/ /

X X

t

s n s n

,

2

2

(1 )z

n

D

,

(1 )

1

p

N n

n N

,

X

n

,

(1 )

p

p p

S

n

,

2 2

2

C z

n

R

, D R ,

X

X

z

,

1X

N n

Nn

, D R , 1

/

D

n

D

D

t

s n

, 1 2 1 2

2 2

1 1 2 2

( ) ( )

/ /

X X

t

n n

, 1 2 1 2

2 2

1 1 2 2

( ) ( )

/ /

X X

t

s n s n

2n

2

i 1

(obs exp )

exp

i i

i

X

, 2 ( 1) ( 1)Xdf c r ,

/

/

regression regression

residual residual

SSE df

F ratio

SSE df

,

2 explained

total

SSE

R

SSE

critical z-value 95% confidence interval (two-tailed) is 1.96

critical z-value 99% confidence interval (two-tailed) is 2.58

critical z-value 95% confidence interval (one-tailed) is 1.65

critical z-value 99% confidence interval (one-tailed) is 2.33