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Regression Analysis Test - Machine Learning
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Questions in this quiz (22)
1All explanatory variables are significant at 90% confidence level

- ATrue
- BFalse
2The most important variable in explaining the target is Years of education

- ATrue
- BFalse
3Living in the South decreases the average wage

- ATrue
- BFalse
4Living in a Metropolitan Statistical Area increases the average wage

- ATrue
- BFalse
5A stepwise method was used to produce the above output

- ATrue
- BFalse
6If we enter a new variable most likely our R Square will increase

- ATrue
- BFalse
7If sample size were 20 observations, we still may rely on the results above

- ATrue
- BFalse
8R Square is the proportion of variance of the target variable explained by the predictors

- ATrue
- BFalse
9Individual significance of variables in Linear Regression is checked with t-student test

- ATrue
- BFalse
10Autocorrelation is produced if we have high correlation between explanatory variables

- ATrue
- BFalse
11Main uses of Linear Regression are simulation, structural analysis and prediction

- ATrue
- BFalse
12A telco company wants to predict a flag field named churn. Linear Regression is the appropriate technique to use

- ATrue
- BFalse
13Heteroscedasticity is having unequal variances of explanatory variables

- ATrue
- BFalse
14If Beta(x2) = 5 * Beta (x1), then x2 is five times more important than x1 in predicting the dependent

- ATrue
- BFalse
15
Average wage “penalty” for Afro-American (AA) workers is on average approx. 18%
In this regression, the LOGARITHM of the yearly wage of workers (log of WAGE) is explained by the AGE of worker in years, father’s education in years and being Afro-American (AA) or not (1=yes / 0= no). (***) Be aware that COMMA “,” is used as decimal separator
- ATrue
- BFalse
16An additional year of worker father’s education yields an average wage increase of 0.027% on average
In this regression, the LOGARITHM of the yearly wage of workers (log of WAGE) is explained by the AGE of worker in years, father’s education in years and being Afro-American (AA) or not (1=yes / 0= no). (***) Be aware that COMMA “,” is used as decimal separator
- ATrue
- BFalse
17We can REJECT the null hypothesis of individual significance for all variables with a 99% confidence
In this regression, the LOGARITHM of the yearly wage of workers (log of WAGE) is explained by the AGE of worker in years, father’s education in years and being Afro-American (AA) or not (1=yes / 0= no). (***) Be aware that COMMA “,” is used as decimal separator
- ATrue
- BFalse
18In this regression, the LOGARITHM of the yearly wage of workers (log of WAGE) is explained by the AGE of worker in years, father’s education in years and being Afro-American (AA) or not (1=yes / 0= no). (***) Be aware that COMMA “,” is used as decimal separator.
Elasticity between Wage and Age is approximately 0.027.
- ATrue
- BFalse
19Comparing coefficients size, AA is clearly the most influential variable
In this regression, the LOGARITHM of the yearly wage of workers (log of WAGE) is explained by the AGE of worker in years, father’s education in years and being Afro-American (AA) or not (1=yes / 0= no). (***) Be aware that COMMA “,” is used as decimal separator.
- ATrue
- BFalse
201 unit increase in Age yields an average 2.7% increase in Wage
In this regression, the LOGARITHM of the yearly wage of workers (log of WAGE) is explained by the AGE of worker in years, father’s education in years and being Afro-American (AA) or not (1=yes / 0= no). (***) Be aware that COMMA “,” is used as decimal separator.
- ATrue
- BFalse
21Confidence interval for AA variable includes the value -0.1
In this regression, the LOGARITHM of the yearly wage of workers (log of WAGE) is explained by the AGE of worker in years, father’s education in years and being Afro-American (AA) or not (1=yes / 0= no). (***) Be aware that COMMA “,” is used as decimal separator.
- ATrue
- BFalse
22Father’s education Beta real value in population might be 20

- ATrue
- BFalse
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- Description
- Informática Quiz on Regression Analysis Test - Machine Learning, created by Angel Intriago on 12/12/2021.
- Author
- Angel Intriago
- Language
- English
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