Compute the Sum of Squared Residuals (SSR), R-squared (R^2), and Root MeanSquared Error from Table 1 (Root MSE). Interpret the R-squared. Table 1• regress size hhincSourcedfMSNumber of obs5,407F(1, 5405)1613.341 263141566Model263141566Prob > F0.0000ResidualR-squaredAdj R-squaredTotal1.1447e+095,406 211749.457Root MSEsizeCoefficientStd. err.tP>|t|[95% conf. interval]hhinc.0082545.000205540.170.000.0078516.0086574-cons800.98359.40491785.170.000782.5461819.4209 The questions below are based on a dataset containing the characteristics of 5,407households. In particular, we will use the following variables:- size: home size, measured in square feet.- hhinc: annual household net income, measured in euros.- owner. dummy variable equal to 1 if the living space is owned, and 0 if the livingspace is rented.- hhsize1: dummy variable equal to 1 if the number of household's members is 1 or2, and 0 otherwise.hhsize2: dummy variable equal to 1 if the number of household's members is 3 or4, and 0 otherwise.hhsize3: dummy variable equal to 1 if the number of household's members is 5 orabove 5, and 0 otherwise.- edu: education level of household's members.The Appendix contains tables with the critical values of the standard normal distribution andthe F distribution.

Answered: Compute the Sum of Squared Residuals…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

Compute the Sum of Squared Residuals (SSR), R-squared (R^2), and Root Mean
Squared Error from Table 1 (Root MSE). Interpret the R-squared.

Table 1
• regress size hhinc
Source
df
MS
Number of obs
5,407
F(1, 5405)
1613.34
1 263141566
Model
263141566
Prob > F
0.0000
Residual
R-squared
Adj R-squared
Total
1.1447e+09
5,406 211749.457
Root MSE
size
Coefficient
Std. err.
t
P>|t|
[95% conf. interval]
hhinc
.0082545
.0002055
40.17
0.000
.0078516
.0086574
-cons
800.9835
9.404917
85.17
0.000
782.5461
819.4209

The questions below are based on a dataset containing the characteristics of 5,407
households. In particular, we will use the following variables:
- size: home size, measured in square feet.
- hhinc: annual household net income, measured in euros.
- owner. dummy variable equal to 1 if the living space is owned, and 0 if the living
space is rented.
- hhsize1: dummy variable equal to 1 if the number of household's members is 1 or
2, and 0 otherwise.
hhsize2: dummy variable equal to 1 if the number of household's members is 3 or
4, and 0 otherwise.
hhsize3: dummy variable equal to 1 if the number of household's members is 5 or
above 5, and 0 otherwise.
- edu: education level of household's members.
The Appendix contains tables with the critical values of the standard normal distribution and
the F distribution.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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