The following table gives the quantity demanded of ice cream (Qic) in kgs per year in Sardinia (Italy), its price (Pic) in $ per kg, consumers’ income (I) in $, the temperature (T) in Celsius, and the price of cappuccino (Pc) in $ per kg:   Year Qic  Pic ($/kg) I ($) T Pc ($/kg) 2000 72000 11 2000 20 14 2001 81000 10 2100 24 15 2002 90000 9 2200 25 15 2003 99000 7 2305 26 16 2004 108000 6 2407 30 17 2005 126000 4 2500 32 18 2006 117000 7 2610 26 16 2007 117000 8 2698 25 16 2008 135000 5 2801 31 18 2009 135000 5 2921 31 18 2010 144000 4 3000 34 20 2011 180000 2 3099 36 21 2012 162000 5 3201 33 19 2013 171000 4 3308 35 21 2014 153000 6 3397 30 18 2015 180000 3 3501 35 22 2016 171000 4 3689 33 20 2017 180000 3 3800 36 23 2018 198000 2 3896 36 25 2019 189000 4 3989 34 23 2020 175000 6 3600 30 18 Note answer question 1.2.3.4. Based on the data provided in the table:         * Using the regression facility in Excel, determine the estimated regression line using a nonlinear multiple regression. Does this model fit the data? Why? If it does, please write the estimated equation. Please, attach the page of the regression analysis output.       * Based on the best model, test the hypothesis that there is no relationship between the demand for ice cream and each one of the independent variables. Also, indicate the statistical significance of each of the independent variables.        * Based on the best model, how much is the coefficient of determination? What does it mean? For the best model, what does the F-test result tell us?       *  Interpret the coefficients of the independent variables based on the best model.        1. Also, describe the demand for ice cream with respect to Pic, I, T and indicate the relationship between ice cream and cappuccino.       2. Determine the point estimate of the demand for ice cream, based on the best regression model, given that the Pic = $10/kg , I = $4,000, T = 30 Celsius, and Pc = $20/kg.        3. Then, construct an approximate 95 percent confidence level prediction interval of the demand for ice cream.       4. If you know that the Durbin-Watson statistic for the data of the this case study is 1.609, what can you conclude about the possibility of autocorrelation?

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The following table gives the quantity demanded of ice cream (Qic) in kgs per year in Sardinia (Italy), its price (Pic) in $ per kg, consumers’ income (I) in $, the temperature (T) in Celsius, and the price of cappuccino (Pc) in $ per kg:

 

Year

Qic 

Pic ($/kg)

I ($)

T

Pc ($/kg)

2000

72000

11

2000

20

14

2001

81000

10

2100

24

15

2002

90000

9

2200

25

15

2003

99000

7

2305

26

16

2004

108000

6

2407

30

17

2005

126000

4

2500

32

18

2006

117000

7

2610

26

16

2007

117000

8

2698

25

16

2008

135000

5

2801

31

18

2009

135000

5

2921

31

18

2010

144000

4

3000

34

20

2011

180000

2

3099

36

21

2012

162000

5

3201

33

19

2013

171000

4

3308

35

21

2014

153000

6

3397

30

18

2015

180000

3

3501

35

22

2016

171000

4

3689

33

20

2017

180000

3

3800

36

23

2018

198000

2

3896

36

25

2019

189000

4

3989

34

23

2020

175000

6

3600

30

18








Note answer question 1.2.3.4.





Based on the data provided in the table:

 

 

 

 

* Using the regression facility in Excel, determine the estimated regression line using a nonlinear multiple regression. Does this model fit the data? Why? If it does, please write the estimated equation. Please, attach the page of the regression analysis output.

 

 

 

* Based on the best model, test the hypothesis that there is no relationship between the demand for ice cream and each one of the independent variables. Also, indicate the statistical significance of each of the independent variables. 

 

 

 

* Based on the best model, how much is the coefficient of determination? What does it mean? For the best model, what does the F-test result tell us?

 

 

 

*  Interpret the coefficients of the independent variables based on the best model. 

 

 

 

1. Also, describe the demand for ice cream with respect to Pic, I, T and indicate the relationship between ice cream and cappuccino.

 

 

 

2. Determine the point estimate of the demand for ice cream, based on the best regression model, given that the Pic = $10/kg , I = $4,000, T = 30 Celsius, and Pc = $20/kg

 

 

 

3. Then, construct an approximate 95 percent confidence level prediction interval of the demand for ice cream.

 

 

 

4. If you know that the Durbin-Watson statistic for the data of the this case study is 1.609, what can you conclude about the possibility of autocorrelation?

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