Question
1 Which of the following is NOT true about linear regression? Review Later Linear regression allows us to predict new values of the independent variable.
1
Which of the following is NOT true about linear regression?
Review Later
Linear regression allows us to predict new values of the independent variable.
Linear regression allows us to model how the target variable changes with the independent variables.
In linear regression, the target variable is a continuous quantity.
Linear regression is used to predict new values of the target variable.
2
The ordinary least squares (OLS) algorithm ________________ .
Review Later
Maximizes the sum of square residuals
Minimizes the sum of square residuals
Minimizes the square of the sum of residuals
Maximizes the square of the sum of residuals
3
Overfitting occurs when _____________.
Review Later
The sum of square residuals is too large
Our model does not have enough complexity
The average of the errors is positive
Our model becomes too specific to the training data
4.
Using multiple linear regression to add in more independent variables ___________.
Review Later
can help explain more variation in the target variable
allows us to fit a non-linear model to the data
allows us to add more observational data to the model
reduces the overfitting of the data
5.
Multicollinearity is the phenomenon where _________________.
Review Later
the independent variables are strongly correlated with the residuals
the target variable is strongly correlated with the residuals
the independent variables are strongly correlated with other independent variables
the target variable is strongly correlated with an independent variable
6
Which of the following isNOTan assumption of ordinary least squares (OLS):
Review Later
Homoscedasticity of Errors
Endogeneity
Random Sampling
Linearity
7
Which assumption of OLS assumes that there is no correlation between the error and the independent variables?
Review Later
Zero Mean Errors
Multicollinearity
Endogeneity
Autocorrelation of Errors
8
A regression analysis between sales (S) (in $1000) and price (P) (in dollars) resulted in the following equation:
S = 50,000 - 8P
The above equation implies that an ___________.
Review Later
increase of $1 in price is associated with a decrease of $8 in sales
increase of $1 in price is associated with a decrease of $8000 in sales
increase of $1 in price is associated with a decrease of $42,000 in sales
increase of $8 in price is associated with an increase of $8,000 in sales
9
Which of the following is the formula for the mean square error?
Review Later
N Elyi - yil O E(vi- yi) 2 1 - E(vi-y)2 O LE(Vi - y 2 O E(vi - y)2Step by Step Solution
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