You are told by someone that they believe the soft drink demand schedule is incorrectly specified. A key variable that is missing is whether the state is on a coastline. Everyone knows that States on the coast will have higher soft drink demand because beach goers absolutely love to take soft drinks to the beach." You will assess this statement by including a dummy variable for a state with an ocean (or Great Lakes Lake) front.

The dataset below can be used in Excel and is required to answer the questions below.

State	Cans	Price	Income	Temp
Alabama	200	2.19	13	66
Arizona	150	1.99	17	62
Arkansas	237	1.93	11	63
California	135	2.59	25	56
Colorado	121	2.29	19	52
Connecticut	118	2.49	27	50
Delaware	217	1.99	28	52
Florida	242	2.29	18	72
Georgia	295	1.89	14	64
Idaho	85	2.39	16	46
Illinois	114	2.35	24	52
Indiana	184	2.19	20	52
Iowa	104	2.21	16	50
Kansas	143	2.17	17	56
Kentucky	230	2.05	13	56
Louisiana	269	1.97	15	69
Maine	111	2.19	16	41
Maryland	217	2.11	21	54
Massachusetts	114	2.29	22	47
Michigan	108	2.25	21	47
Minnesota	108	2.31	18	41
Mississippi	248	1.98	10	65
Missouri	203	1.94	19	57
Montana	77	2.31	19	44
Nebraska	97	2.28	16	49
Nevada	166	2.19	24	48
New Hampshire	177	2.27	18	35
New Jersey	143	2.31	24	54
New Mexico	157	2.17	15	56
New York	111	2.43	25	48
North Carolina	330	1.89	13	59
North Dakota	63	2.33	14	39
Ohio	165	2.21	22	51
Oklahoma	184	2.19	16	82
Oregon	68	2.25	19	51
Pennsylvania	121	2.31	20	50
Rhode Island	138	2.23	20	50
South Carolina	237	1.93	12	65
South Dakota	95	2.34	13	45
Tennessee	236	2.19	13	60
Texas	222	2.08	17	69
Utah	100	2.37	16	50
Vermont	64	2.36	16	44
Virginia	270	2.04	16	58
Washington	77	2.19	20	49
West Virginia	144	2.11	15	55
Wisconsin	97	2.38	19	46
Wyoming	102	2.31	19	46

The states designated (by someone) as Ocean (and GreatLakes) states are

Population by state is:

State	Population
Alabama	4,903,185
Arizona	7,278,717
Arkansas	3,017,825
California	39,512,223
Colorado	5,758,736
Connecticut	3,565,287
Delaware	973,764
Florida	21,477,737
Georgia	10,617,423
Idaho	1,787,065
Illinois	12,671,821
Indiana	6,732,219
Iowa	3,155,070
Kansas	2,913,314
Kentucky	4,467,673
Louisiana	4,648,794
Maine	1,344,212
Maryland	6,045,680
Massachusetts	6,949,503
Michigan	9,986,857
Minnesota	5,639,632
Mississippi	2,976,149
Missouri	6,137,428
Montana	1,068,778
Nebraska	1,934,408
Nevada	3,080,156
New Hampshire	1,359,711
New Jersey	8,882,190
New Mexico	2,096,829
New York	19,453,561
North Carolina	10,488,084
North Dakota	762,062
Ohio	11,689,100
Oklahoma	3,956,971
Oregon	4,217,737
Pennsylvania	12,801,989
Rhode Island	1,059,361
South Carolina	5,148,714
South Dakota	884,659
Tennessee	6,833,174
Texas	28,995,881
Utah	3,205,958
Vermont	623,989
Virginia	8,535,519
Washington	7,614,893
West Virginia	1,792,147
Wisconsin	5,822,434
Wyoming	578,759

The demand specifications below are guides to answer the questions below.

DEMAND SPECIFICATION

(1) Cans = +1*Price +2*Income +3*Temp +4*Ocean.

Use Excel Data Analysis Regression to estimate the demand function.

DEMAND SPECIFICATION (#2b)

Use the same Soft Drink Demand data as in question #1 to estimate a multiplicative specification of the demand function with the Ocean dummy variable included. Consider the following multiplicative soft drink demand specification:

(2a) Cans = *Price¹*Income²*Temp³*e^4*Ocean.

Use Excel Data Analysis to estimate the demand function.Transform the data into natural log variables. The log-linear equation to estimate is:

(2b) lnCans = ln + ₁*lnPrice + ₂*lnIncome + ₃*lnTemp + ₄*Ocean.

The math notation "ln" refers to natural log.

DEMAND SPECIFICATION (#3)

Suppose someone has made the statement "We know that the Soft drink Demand Function is not correctly specified. Everyone knows a demand function should include the potential number of customers in the relevant market. Thus, we should include state populations in the demand specification".Population by state is provided below.

DEMAND SPECIFICATION (#4b)

Consider the following multiplicative soft drink demand specification:

(4a) Cans = *Price¹*Income²*Temp³*Population⁴.

Use Excel Data Analysis to estimate this multiplicative demand function.Transform the data into natural log variables to estimate the multiplicative equation. The log-linear equation to estimate is:

(4b) lnCans = ln +1*lnPrice +2*lnIncome +3*lnTemp +4*lnPopulation.

DEMAND SPECIFICATION (#5)

Consider the following linear soft drink demand specification:

(5) Cans = +1*Price +2*Income +3*Temp +4*Population +5*Ocean.

Use Excel Data Analysis to estimate this linear demand function which includes both Population and Ocean.

DEMAND SPECIFICATION (#6b)

Consider the following multiplicative soft drink demand specification:

(6a) Cans = *Price¹*Income²*Temp³*Population⁴*e^5*Ocean.

Use Excel Data Analysis to estimate the multiplicative demand function. Transform the data into natural log variables to estimate the multiplicative equation. The log-linear equation to estimate is:

(6b) lnCans = ln +1*lnPrice +2*lnIncome +3*lnTemp +4*lnPopulation +5*Ocean.

QUESTION 1

Refer to the Excel Regression output for Equation (1) Cans = + 1*Price + 2*Income + 3*Temp + 4*Ocean. What is the estimated coefficient for Price?

	A.	-124.91.
	B.	-186.53.
	C.	-233.88.
	D.	-344.25.

QUESTION 2

Refer to the Regression output for Equation (1). At what level is the coefficient for Price statistically significant?

	A.	.01 level.
	B.	.05 level.
	C.	.10 level.
	D.	Not statistically significant at any of the above levels.

QUESTION 3

Refer to the output for Equation (2b) lnCans = ln + 1*lnPrice + 2*lnIncome + 3*lnTemp + 4*Ocean. What is the estimated price elasticity of demand?

	A.	-.4.68.
	B.	-3.13.
	C.	-2.76.
	D.	-2.15.
	E.	-1.13.

QUESTION 4

Refer to the output for Equation (3) Cans = + 1*Price + 2*Income + 3*Temp + 4*Population.What is the estimated coefficient for Price?

	A.	-.278.07.
	B.	-223.15.
	C.	-194.34.
	D.	-182.65.
	E.	-118.28.

QUESTION 5

Refer to the output for Equation (3) Cans = + 1*Price + 2*Income + 3*Temp + 4*Population. At what level is the coefficient for Population statistically significant?

	A.	.01 level.
	B.	.05 level.
	C.	.10 level.
	D.	Not statistically significant at any of the above levels.

QUESTION 6

Refer to the output for Equation (4b) lnCans = ln + 1*lnPrice + 2*lnIncome + 3*lnTemp + 4*lnPopulation. At what level is the coefficient for Population statistically significant? Write your answer in 1a above.

	A.	.01 level.
	B.	.05 level.
	C.	.10 level.
	D.	Not statistically significant at any of the above levels.

QUESTION 7

Refer to the output for Equation (4b) lnCans = ln + 1*lnPrice + 2*lnIncome + 3*lnTemp + 4*lnPopulation. If there is a 1% increase in Price, by what percentage will Cans decrease?

	A.	3.32.
	B.	.2.98.
	C.	.2.13.
	D.	1.46.

QUESTION 8

Refer to the output for Equation (5) Cans = + 1*Price + 2*Income + 3*Temp + 4*Population + 5*Ocean. What can we conclude?

	A.	Both Population and Ocean are statistically significant at better than the .05 level.
	B.	Population is statistically significant at better than the .10 level but Ocean is not statistically significant at the .10 level.
	C.	Ocean is statistically significant at better than the .05 level but Population is not statistically significant at the .10 level.
	D.	Population is statistically significant at better than the .01 level but Ocean is not statistically significant at the .10 level.

QUESTION 9

Refer to the output for Equation (6b) lnCans = ln + 1*lnPrice + 2*lnIncome + 3*lnTemp + 4*lnPopulation + 5*Ocean. What can we conclude?

	A.	Both Population and Ocean are statistically significant at better than the .05 level.
	B.	Population is statistically significant at better than the .10 level but Ocean is not statistically significant at the .10 level.
	C.	Ocean is statistically significant at better than the .01 level but Population is not statistically significant at the .10 level.
	D.	Population is statistically significant at better than the .01 level but Ocean is not statistically significant at the .10 level.
	E.	NeitherPopulation nor Ocean is statistically significant at better than the .10.

I only need help with question 9 please