1. Explain how can test the joint hypothesis that ? 2 = ? 3 = 0 related to average income 2. Explain how you can test the joint hypothesis that none of the variables has an effect upon air quality? Do you accept or reject this null hypothesis in the above Stata output?

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter10: Statistics
Section10.3: Measures Of Spread
Problem 1GP
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1. Explain how can test the joint hypothesis that ? 2 = ? 3 = 0 related to average income

2. Explain how you can test the joint hypothesis that none of the variables has an effect upon air quality? Do you accept or reject this null hypothesis in the above Stata output?

The data set AIRQ contains observations for 30 standard metropolitan statistical areas
(SMSAS) in California for 1972 on the following variables.
indicator of air quality (The lower the better)
value added of companies (in 1000 US$)
amount of rain (in inches)
dummy variable, 1 for (SMSAS) at the coast, 0 for others
population density (per square mile)
average income per head (in US$)
airq
vala
rain
сoas
dens
тedi
reg airq vala rain coas dens medi
df
Number of obs
30
2.98
Source
MS
F( 5,
Prob > F
24) =
Model
Residual
8723. 84625
14058.4538
1744.76925
0.0313
R-squared
Adj R-squared =
0. 3829
0.2544
24.203
24
585.768906
Total
22782.3
29
785. 596552
Root MSE
airq
Coef.
std. Err.
P>|t|
[95% Conf. Interval]
vala
rain
0. 699
.0008834
.2506988
-33. 3983
-.0010734
.0005545
0. 39
0.73
-3.19
-0. 66
0.65
.0055399
.9596857
-11. 81504
.0022562
-.0037731
-.458288
-54.98156
-.0044237
-.0012003
80. 29141
3435183
0.473
0. 004
0. 515
0. 521
сoas
10.45752
dens
medi
.0016233
.0022769
.0008503
.0023093
_cons
111.9347
15. 33179
7.30
0.000
143. 5779
Transcribed Image Text:The data set AIRQ contains observations for 30 standard metropolitan statistical areas (SMSAS) in California for 1972 on the following variables. indicator of air quality (The lower the better) value added of companies (in 1000 US$) amount of rain (in inches) dummy variable, 1 for (SMSAS) at the coast, 0 for others population density (per square mile) average income per head (in US$) airq vala rain сoas dens тedi reg airq vala rain coas dens medi df Number of obs 30 2.98 Source MS F( 5, Prob > F 24) = Model Residual 8723. 84625 14058.4538 1744.76925 0.0313 R-squared Adj R-squared = 0. 3829 0.2544 24.203 24 585.768906 Total 22782.3 29 785. 596552 Root MSE airq Coef. std. Err. P>|t| [95% Conf. Interval] vala rain 0. 699 .0008834 .2506988 -33. 3983 -.0010734 .0005545 0. 39 0.73 -3.19 -0. 66 0.65 .0055399 .9596857 -11. 81504 .0022562 -.0037731 -.458288 -54.98156 -.0044237 -.0012003 80. 29141 3435183 0.473 0. 004 0. 515 0. 521 сoas 10.45752 dens medi .0016233 .0022769 .0008503 .0023093 _cons 111.9347 15. 33179 7.30 0.000 143. 5779
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