2. From the data in the table below, estimate two regression models using a calc
ID: 3277754 • Letter: 2
Question
2. From the data in the table below, estimate two regression models using a calculator. Show your work in a table (see slide 13) Model 1: Gold price,-, + 2CPL + ut Model 2: NYSE Index.-A+ 2CPle+ ut Gold Prices, Consumer Price Index and the New York Stock Exchange, 1977-1991 YEAR PRICE CPI NYSE 147.98 193.44 307.62 612.51 459.61 376.01 423.83 53.69 53.70 58.32 68.10 74.02 68.93 92.63 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 60.60 65.20 72.60 82.40 90.90 96.50 99.60 360.29103.90 92.46 317.30 107.60 108.90 367.87109.60 136.00 446.50 113.60 161.70 436.93 118.30 149.91 381.28 124.00 180.02 384.08 130.70 183.46 362.04136.20 206.33 where YEAR: Year GOLD PRICE: Price of Gold at New York, $ Per Troy Ounce CPI Consumer Price Index, 1982-1984: 100 NYSE New York Stock Exchange Index, December 31, 1965-100 For each model a) Find 1 and 2, their standard errors and r2. b) write down the equation in the format Yi = + RMExplanation / Answer
Answer:
Model 1
Regression Analysis
r²
0.150
n
15
r
0.388
k
1
Std. Error
104.694
Dep. Var.
price
ANOVA table
Source
SS
df
MS
F
p-value
Regression
25,188.9072
1
25,188.9072
2.30
.1535
Residual
142,490.6951
13
10,960.8227
Total
167,679.6023
14
Regression output
confidence interval
variables
coefficients
std. error
t (df=13)
p-value
95% lower
95% upper
Intercept
186.1833
125.4039
1.485
.1615
-84.7353
457.1019
CPI
1.8420
1.2151
1.516
.1535
-0.7830
4.4670
The regression equation is
Price =186.1833 + 1.8420*CPI
Standard error=104.694
R square =0.150
Model 2
Regression Analysis
r²
0.868
n
15
r
0.932
k
1
Std. Error
19.842
Dep. Var.
NYSE
ANOVA table
Source
SS
df
MS
F
p-value
Regression
33,663.9722
1
33,663.9722
85.51
4.43E-07
Residual
5,118.0592
13
393.6969
Total
38,782.0314
14
Regression output
confidence interval
variables
coefficients
std. error
t (df=13)
p-value
95% lower
95% upper
Intercept
-102.0606
23.7668
-4.294
.0009
-153.4056
-50.7155
CPI
2.1294
0.2303
9.247
4.43E-07
1.6319
2.6269
The regression equation is
NYSE = -102.0606 + 2.1294*CPI
Standard error=19.842
R square =0.868
Regression Analysis
r²
0.150
n
15
r
0.388
k
1
Std. Error
104.694
Dep. Var.
price
ANOVA table
Source
SS
df
MS
F
p-value
Regression
25,188.9072
1
25,188.9072
2.30
.1535
Residual
142,490.6951
13
10,960.8227
Total
167,679.6023
14
Regression output
confidence interval
variables
coefficients
std. error
t (df=13)
p-value
95% lower
95% upper
Intercept
186.1833
125.4039
1.485
.1615
-84.7353
457.1019
CPI
1.8420
1.2151
1.516
.1535
-0.7830
4.4670
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