Question 1 (1 point) Using the attached dataset (in a separate Excel file and al

Question

Question 1 (1 point)

Using the attached dataset (in a separate Excel file and also included here). If we regress wage on age, years of schooling, public sector, tenure, which of the following coefficients will NOT be statistically significant (recall, we consider 90% or higher when we consider statistical significance). Hint, you want to look for the coefficient with the highest p-value.

Question 1 options:

Years of schooling

Age

Tenure on the job

The intercept

Question 2 (1 point)

Again, please use the data from the attached Excel file or the previous question.

The regression of age on years of schooling, public, tenure on the job, does not exhibit any serious multicolinearity concerns.

Question 2 options:

Save

Question 3 (1 point)

Multicollinearity occurs when two or more regressors are highly correlated with each other.

Question 3 options:

Question 4 (1 point)

The plot of residuals included here suggests the presence of which problem? (the plot is also included in the Excel file)

Question 4 options:

heteroscedasticity

multicollinearity

wrongly formulated model

None of the above

Question 5 (1 point)

Which of the following problems is illustrated by the below residuals' plot?

Question 5 options:

Outlier

Heteroscedasticity

Improperly formulated model

None of the above

wage in dollars age of the worker (in years) years of schooling completed by the worker (years) public sector (1 if in public sector, 0 if in private) tenure on the job (years on the current job) 17.9 35 17 1 4.4 30.12 58 13 0 7.32 18.3 20 12 0 3.8 19.68 32 17 1 2.28 28.96 59 15 1 2.36 27.82 53 11 1 6.12 26 50 13 1 6 25 40 18 0 4.6 22.56 24 12 0 5.96 13.76 24 13 1 1.96 25.28 52 11 1 6.08 20.12 38 15 1 3.52 28.82 63 15 0 3.52 20.06 19 12 0 6.76 14.98 27 12 1 2.08 18.52 38 14 1 2.52 29.1 55 12 0 4.2 25.3 40 16 0 7.6 26.16 54 10 0 7.16 23.18 42 16 1 4.68 18.94 36 16 0 1.44 20.4 45 15 1 1.8 21.84 46 10 1 4.84 26.38 57 11 0 5.28 31.84 61 14 0 7.44 19.56 44 17 0 1.76 24.78 37 11 1 7.48 25.06 39 16 1 4.56 21.12 48 10 1 1.92 30.48 62 16 1 8.48 21.8 20 15 0 4.8 31.62 63 11 1 7.52 28.1 65 9 0 2.6 30.36 64 13 1 2.56 14.98 17 18 0 3.68 26.12 53 10 1 4.12 21.92 38 11 0 4.52 28.16 64 11 1 4.56 31.8 60 16 1 6.4 Residual 20 15 10 10 40 . 50 -10 15 20

Explanation / Answer

q1)the largest p value is 0.317 and corresponds to years of schooling

so option a correct answer

q2)  larger VIF indicate more collinearity, . All the VIF values here are very close to 1 (the minimum VIF value),

answer is true

q3) its basic defintion is given

so its true

q4) heteroscedasticity

here variability of a variable is unequal across the range of values so it is option a

q5) outlier

it is a point that is distant from other observations. may be due to variability

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