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Research Question 1: Is there a linear relationship between the quality of food

ID: 3222989 • Letter: R

Question

Research Question 1: Is there a linear relationship between the quality of food ratings (Food) and the average cost of dinner for two (Cost). [Cost is the response variable.]

Is the sample size large enough? Explain.

Report relevant sample statistics.

Draw and interpret appropriate graphs for (a) each variable separately and (b) the relationship between the two variables.

Write the null and alternative hypotheses.

Write decision rules for both the critical and p-value approaches.

Use R to obtain the test statistic and p-value.

What is the appropriate statistical decision (Reject or FTR Ho)?

Organize the df, sums of squares, etc. into a summary ANOVA table.

Compute and interpret the coefficient of determination.

Research Question 2: Is there a linear relationship between the ambiance ratings (Ambiance) and the average cost of dinner for two (Cost). [Cost is the response variable.] Report relevant sample statistics.

Is the sample size large enough? Explain.

Draw and interpret appropriate graphs for (a) each variable separately and (b) the relationship between the two variables.

Write the null and alternative hypotheses.

Write decision rules for both the critical and p-value approaches.

Use R to obtain the test statistic and p-value.

What is the appropriate statistical decision (Reject or FTR Ho)?

Organize the df, sums of squares, etc. into a summary ANOVA table.

Compute and interpret the coefficient of determination.

Location Food Ambiance Service Cost City 22 14 19 33 City 20 15 20 26 City 23 19 21 43 City 19 18 18 32 City 24 16 18 44 City 22 22 21 44 City 22 20 20 50 City 20 19 19 42 City 21 17 19 44 City 20 18 18 36 City 23 22 24 61 City 20 19 20 50 City 21 19 21 51 City 24 19 21 50 City 25 23 23 76 City 22 21 21 53 City 23 15 22 44 City 26 22 24 77 City 21 23 21 57 City 24 15 19 43 City 21 15 19 29 City 23 16 16 34 City 25 21 26 77 City 22 20 21 50 City 26 25 24 74 City 23 21 21 56 City 22 19 17 67 City 26 20 23 57 City 26 23 25 66 City 24 23 24 80 City 22 23 23 68 City 24 16 23 42 City 20 17 19 48 City 25 19 23 60 City 23 20 21 35 City 21 19 22 45 City 20 16 18 32 City 23 15 18 25 City 26 24 24 74 City 21 18 18 43 City 22 16 19 39 City 19 23 21 55 City 24 19 21 65 City 23 16 20 35 City 24 26 22 61 City 21 17 18 37 City 21 17 19 54 City 23 19 22 41 City 23 19 21 33 City 23 14 19 27 Suburban 24 20 22 47 Suburban 22 18 22 48 Suburban 18 13 18 35 Suburban 22 23 20 59 Suburban 22 18 24 44 Suburban 23 25 24 51 Suburban 20 12 18 37 Suburban 19 18 19 36 Suburban 22 19 21 43 Suburban 27 21 27 52 Suburban 19 14 18 34 Suburban 22 11 19 38 Suburban 24 22 24 51 Suburban 19 15 19 34 Suburban 21 23 21 51 Suburban 21 19 21 34 Suburban 23 19 23 51 Suburban 23 20 22 56 Suburban 21 13 19 26 Suburban 24 19 22 34 Suburban 20 18 20 34 Suburban 24 22 24 44 Suburban 23 17 22 40 Suburban 23 16 21 31 Suburban 23 18 22 54 Suburban 19 12 22 41 Suburban 22 17 21 50 Suburban 26 27 24 71 Suburban 22 21 23 60 Suburban 19 15 17 37 Suburban 21 12 20 27 Suburban 26 18 22 34 Suburban 22 25 21 48 Suburban 21 21 21 39 Suburban 20 20 20 44 Suburban 22 18 22 41 Suburban 23 20 19 37 Suburban 24 21 23 47 Suburban 23 27 22 67 Suburban 24 24 22 68 Suburban 26 17 24 49 Suburban 22 22 19 29 Suburban 24 18 22 33 Suburban 20 19 20 39 Suburban 26 19 23 39 Suburban 22 15 21 28 Suburban 18 20 18 46 Suburban 26 27 25 70 Suburban 25 26 23 60 Suburban 22 25 22 52

Explanation / Answer

Is there a linear relationship between the quality of food ratings (Food) and the average cost of dinner for two (Cost). [Cost is the response variable.]

Answer:

For checking the linear relationship or association exists between the two variables we have to find the sample correlation coefficient. The correlation coefficient between the two variables quality of food ratings and the average cost of dinner for two is given as 0.489538, this means there is a considerable positive linear relationship or association exists between the two variables quality of food ratings and the average cost of dinner for two. We have to check whether the given correlation coefficient is significant or not.

Is the sample size large enough? Explain.

Answer:

The given sample size is 100, so it is adequate sample size for using the different tests of hypothesis or regression analysis because as per thumb rule, we need the sample size at least 30 for making inference.

Report relevant sample statistics

Answer:

The relevant sample statistics includes the descriptive statistics which are given as below:

Descriptive Summary

Food

Mean

22.42

Median

22

Mode

22

Minimum

18

Maximum

27

Range

9

Variance

4.3067

Standard Deviation

2.0753

Coeff. of Variation

9.26%

Skewness

0.0569

Kurtosis

-0.5085

Count

100

Standard Error

0.2075

Descriptive Summary

Cost

Mean

46.85

Median

44

Mode

44

Minimum

25

Maximum

80

Range

55

Variance

180.2500

Standard Deviation

13.4257

Coeff. of Variation

28.66%

Skewness

0.5957

Kurtosis

-0.3276

Count

100

Standard Error

1.3426

Draw and interpret appropriate graphs for (a) each variable separately and (b) the relationship between the two variables.

Answer:

Here, we have to draw the scatter plot for the given two variables. The scatter plot is given as below:

From the above scatter plot it is observed that there is no any significant relationship exists between the given two variables food and cost.

Write the null and alternative hypotheses.

Answer:

The null and alternative hypothesis for this test is given as below:

Null hypothesis: H0: There is no any significant linear relationship exists between the dependent variable cost and independent variable food.

Alternative hypothesis: Ha: There is a significant linear relationship exists between the dependent variable cost and independent variable food.

The regression analysis for more reference is given as below:

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.489538448

R Square

0.239647892

Adjusted R Square

0.231889197

Standard Error

11.76656161

Observations

100

ANOVA

df

SS

MS

F

P-value

Regression

1

4276.456727

4276.456727

30.88765483

0

Residual

98

13568.29327

138.4519722

Total

99

17844.75

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

-24.15508021

12.83013008

-1.88268397

0.062709399

-49.61605515

1.305894719

Food

3.167041936

0.569851042

5.557666311

2.35673E-07

2.036191119

4.297892754

Descriptive Summary

Food

Mean

22.42

Median

22

Mode

22

Minimum

18

Maximum

27

Range

9

Variance

4.3067

Standard Deviation

2.0753

Coeff. of Variation

9.26%

Skewness

0.0569

Kurtosis

-0.5085

Count

100

Standard Error

0.2075

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