The Economy 2020 to 2022.csv is given as follows: Please just solve for question 5,the solution to question 4 is also given as follows.YearMonthN_WeekPCEPICPIAUCSLICSA_Week1ICSA_Week2ICSA_Week3ICSA_Week4ICSA_Week5202014110.944259.037217000203000211000200000 202025111.07259.248191000186000190000196000190000202034110.824258.12418600022100029140005946000 202044110.237256.0926137000486900042010003446000 202055110.353255.86827960002335000217600019210001639000202064110.746256.9861575000147300014670001446000 202074111.072258.2781413000146800013930001260000 202085111.411259.4111044000884000927000876000881000202094111.613260.029892000861000859000795000 2020105111.648260.2867850008390008040007760007730002020114111.666260.813737000738000793000737000 2020124112.15262.035873000886000815000773000 202115112.583262.65803000890000844000799000803000202124112.961263.638812000802000702000704000 202134113.632264.914693000699000627000658000 202144114.238266.67645000571000566000574000 202155114.819268.444517000494000467000441000427000202164115.458270.559420000429000424000405000 202175115.986271.764403000391000424000411000414000202184116.444272.87416000405000395000381000 202194116.808274.028361000363000380000376000 2021105117.479276.5223400003170003100002940002800002021114118.2278.711279000265000244000240000 2021124118.841280.887228000228000220000211000 202215119.469282.599224000238000240000222000214000202224120.178284.61191000209000198000182000 202234121.321287.472198000177000166000171000 202245121.563288.611168000186000185000181000202000202254122.3291.268197000218000211000202000 202264123.512294.728232000231000233000231000 202275123.397294.628236000244000261000237000248000202284123.728295.32252000245000237000228000 202294124.154296.539218000208000209000190000 2022105124.666297.9872190002260002140002180002180002022114124.873298.598226000223000241000226000 2022124125.124298.99231000212000216000225000 Question 5The Consumer Price Index for January 2023 is 300.536. Based on your linear regression model inQuestion 4, what is your prediction for the Personal Consumption Expenditure for January 2023?What is the 95% confidence interval? Please round your answers to the fourth decimal place.Prediction=95% Confidence Interval= (Question 4Use the Economy 2020 to 2022.csv to train a linear regression model of Personal ConsumptionExpenditure (the dependent variable) on Consumer Price Index (the independent variable). What isthe Intercept? What is the Slope? Please round your answers to the fourth decimal place.Intercept =Slope Step 1: Data > Data Analysis > Regression analysis > OKStep 2: Input values as given:02✓IX✓fx PCE9101113141316313233353637384Multiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVARegressionResidualTotalсInterceptCPIDPCEAnswer:Regression Statistics110.944111.070 259.248110.824 238.124110237 256.092110.353 255.868110.746 256.986111072CPI111.411 259.411111.613260.029111.648260.256111.666 260.813112.150262.033112.583262.630112.961 263.638113.632 261.914114.238 266.670114.819 268.444115.458 270.559115.995 271.764116.444 272.870116.808 274.028117.479 276.522115.200 278.711118.841 290.587E119.469 282.599120.178284.600121.321 287.472121.563 288.611122.300291 268123.512123.397123.728294.728294.625295.320124.154 296.539124.666124.873 298.598125.124298.990Sheet1 +0.9993651740.9987307510.9986934210.185936263ofIntercept = 22.0882Slope = 0.344536F13435RegressionInputFrom the above steps, we derive the following table in Excel:SUMMARY OUTPUTInput Y Range:Input X Range:HLabelsConfidence LevelOutput optionsO Output Range:New Worksheet PlyNew WorkbookResidualsBesidualsStandardized ResidualsNormal ProbabilityNormal Probability PlotsSSMSF924.9299102 924.9299102 26753.501291.175457993 0.034572294926.1053682Coefficients Standard ErrorP-valueStat22.08820313 0.578293023 38.19552071 1.63817E-290.344535308 0.002106412 163.5649758 7.8264E-51InterpretationFrom the regression summary table above. we see thatIntercept = 22.08820313CPI (Slope) = 0.34453530895J$0$150537SEST:$E$37Constantis Zero$G$2KResigual PlotsLine Fit PlotsSignificance F7.8264E-51LMN?OK0CancelHelpXLower 95% Upper 95%Lower 95.0% Upper 95.0%20.91297031 23.26343595 20.91297031 23.263435950.340254563 0.348816053 0.340254563 0.348816053

The mean of your estimate plus and minus the range of that estimate constitutes a confidence…

Answered: The Consumer Price Index for January…

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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The Economy 2020 to 2022.csv is given as follows: Please just solve for question 5,the solution to question 4 is also given as follows.

Year	Month	N_Week	PCEPI	CPIAUCSL	ICSA_Week1	ICSA_Week2	ICSA_Week3	ICSA_Week4	ICSA_Week5
2020	1	4	110.944	259.037	217000	203000	211000	200000
2020	2	5	111.07	259.248	191000	186000	190000	196000	190000
2020	3	4	110.824	258.124	186000	221000	2914000	5946000
2020	4	4	110.237	256.092	6137000	4869000	4201000	3446000
2020	5	5	110.353	255.868	2796000	2335000	2176000	1921000	1639000
2020	6	4	110.746	256.986	1575000	1473000	1467000	1446000
2020	7	4	111.072	258.278	1413000	1468000	1393000	1260000
2020	8	5	111.411	259.411	1044000	884000	927000	876000	881000
2020	9	4	111.613	260.029	892000	861000	859000	795000
2020	10	5	111.648	260.286	785000	839000	804000	776000	773000
2020	11	4	111.666	260.813	737000	738000	793000	737000
2020	12	4	112.15	262.035	873000	886000	815000	773000
2021	1	5	112.583	262.65	803000	890000	844000	799000	803000
2021	2	4	112.961	263.638	812000	802000	702000	704000
2021	3	4	113.632	264.914	693000	699000	627000	658000
2021	4	4	114.238	266.67	645000	571000	566000	574000
2021	5	5	114.819	268.444	517000	494000	467000	441000	427000
2021	6	4	115.458	270.559	420000	429000	424000	405000
2021	7	5	115.986	271.764	403000	391000	424000	411000	414000
2021	8	4	116.444	272.87	416000	405000	395000	381000
2021	9	4	116.808	274.028	361000	363000	380000	376000
2021	10	5	117.479	276.522	340000	317000	310000	294000	280000
2021	11	4	118.2	278.711	279000	265000	244000	240000
2021	12	4	118.841	280.887	228000	228000	220000	211000
2022	1	5	119.469	282.599	224000	238000	240000	222000	214000
2022	2	4	120.178	284.61	191000	209000	198000	182000
2022	3	4	121.321	287.472	198000	177000	166000	171000
2022	4	5	121.563	288.611	168000	186000	185000	181000	202000
2022	5	4	122.3	291.268	197000	218000	211000	202000
2022	6	4	123.512	294.728	232000	231000	233000	231000
2022	7	5	123.397	294.628	236000	244000	261000	237000	248000
2022	8	4	123.728	295.32	252000	245000	237000	228000
2022	9	4	124.154	296.539	218000	208000	209000	190000
2022	10	5	124.666	297.987	219000	226000	214000	218000	218000
2022	11	4	124.873	298.598	226000	223000	241000	226000
2022	12	4	125.124	298.99	231000	212000	216000	225000

Question 5
The Consumer Price Index for January 2023 is 300.536. Based on your linear regression model in
Question 4, what is your prediction for the Personal Consumption Expenditure for January 2023?
What is the 95% confidence interval? Please round your answers to the fourth decimal place.
Prediction=
95% Confidence Interval= (
Question 4
Use the Economy 2020 to 2022.csv to train a linear regression model of Personal Consumption
Expenditure (the dependent variable) on Consumer Price Index (the independent variable). What is
the Intercept? What is the Slope? Please round your answers to the fourth decimal place.
Intercept =
Slope

Step 1: Data > Data Analysis > Regression analysis > OK
Step 2: Input values as given:
02
✓IX✓
fx PCE
9
10
11
13
14
13
16
31
32
33
35
36
37
38
4
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
с
Intercept
CPI
D
PCE
Answer:
Regression Statistics
110.944
111.070 259.248
110.824 238.124
110237 256.092
110.353 255.868
110.746 256.986
111072
CPI
111.411 259.411
111.613
260.029
111.648
260.256
111.666 260.813
112.150
262.033
112.583
262.630
112.961 263.638
113.632 261.914
114.238 266.670
114.819 268.444
115.458 270.559
115.995 271.764
116.444 272.870
116.808 274.028
117.479 276.522
115.200 278.711
118.841 290.587
E
119.469 282.599
120.178
284.600
121.321 287.472
121.563 288.611
122.300
291 268
123.512
123.397
123.728
294.728
294.625
295.320
124.154 296.539
124.666
124.873 298.598
125.124
298.990
Sheet1 +
0.999365174
0.998730751
0.998693421
0.185936263
of
Intercept = 22.0882
Slope = 0.3445
36
F
1
34
35
Regression
Input
From the above steps, we derive the following table in Excel:
SUMMARY OUTPUT
Input Y Range:
Input X Range:
H
Labels
Confidence Level
Output options
O Output Range:
New Worksheet Ply
New Workbook
Residuals
Besiduals
Standardized Residuals
Normal Probability
Normal Probability Plots
SS
MS
F
924.9299102 924.9299102 26753.50129
1.175457993 0.034572294
926.1053682
Coefficients Standard Error
P-value
Stat
22.08820313 0.578293023 38.19552071 1.63817E-29
0.344535308 0.002106412 163.5649758 7.8264E-51
Interpretation
From the regression summary table above. we see that
Intercept = 22.08820313
CPI (Slope) = 0.344535308
95
J
$0$150537
SEST:$E$37
Constantis Zero
$G$2
K
Resigual Plots
Line Fit Plots
Significance F
7.8264E-51
L
M
N
?
OK
0
Cancel
Help
X
Lower 95% Upper 95%
Lower 95.0% Upper 95.0%
20.91297031 23.26343595 20.91297031 23.26343595
0.340254563 0.348816053 0.340254563 0.348816053

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