Question

1. If we add k indicator variables to a regression model for a categorical variable with k levels, the regression tool will return one coefficient estimate of 0.00 because:

a. The k variables are not independent b. The k variables are independent

2. If we add up to 3rd order polynomial terms to a regression model (e.g., x, x^2 and x^3) it will allow the relationship between X and Y to change direction 3 times.

a. True b. False

3. The coefficient of an indicator variable can be interpreted as the average difference from (i.e., relative to) the category level that was left out (i.e., was coded as 0s).

a. True b. False

Answer #1

Answer True or False. When we add an X3 variable to a model that
previously included only a single X variable (i.e., what we called
the Simple Regression Model in Chapters 1 and 2), the Total Sum of
Squares will decrease.
Answer True or False. When we add an X3 variable to a model that
previously included only a single X variable (i.e., what we called
the Simple Regression Model in Chapters 1 and 2), the Total Sum of
Squares...

QUESTION 30
True or False: We can include a categorical variable (such as
region) in a multivariate model in the same way we include a
continuous variable.
True
False
2.5 points
QUESTION 31
True or False: We fail to reject the null hypothesis if the test
statistic is greater than the critical value.
True
False
2.5 points
QUESTION 32
True or False: We necessarily do not have an omitted variable bias
problem the omitted variable is uncorrelated with...

Answer true or false: When we add an X3 variable to a model that
previously included only a single X variable (i.e. what we called
the Simple Regression model in chapter 1 and 2), the R-Squared can
increase, decrease, or remain the same as the value from the
single-X model.

QUESTION 33
True or False: When conducting analysis using categorical
variables, we include a dummy variable for every category covered
by the categorical variable.
True
False
QUESTION 34
We are analyzing the effects of regime type on corruption rates
with the following model: Corruption = 10 - 0.1 GDP (per capita) -
2.0Democracy where Corruption is an index of corruption, GDP (per
capita) is measured in thousands of dollars, and Democracy is a
dummy variable that is equal to one...

In a linear regression model, you add a categorical variable of
city that has 60 different cities.This leads to:
(i) Overfitting of your model
(ii) Underfitting of your model
(iii) Reduction in the Degrees of freedom of your model
(i) only
(ii) only
(iii) only
(i) and (ii)
(i) and (iii)

Suppose we have a regression model with 3 independent variables
and an R2 value of 0.65 and an adjusted R2
value of 0.61. When we add a fourth independent variable, the new
R2 value is 0.73 and the new adjusted R2
value is 0.54. What can we conclude about this newly added
independent variable?
Group of answer choices
The new independent variable improves our model because
R-squared increased
The new independent variable improves our model because the
adjusted R-squared value...

With a multi-variable linear regression model how can we decide
which independent variables to remove from the model?

Regression ____ (b values) indicate how much influence each
independent variable has on the dependent variable.
Regression analysis serves two main purposes: to define the
relationship between variables and to ____ values of the dependent
variable using what we know about the existing correlation between
the variables.
The coefficient of multiple determination, R^2, is interpreted
as the percentage of ____ in the dependent variable that is
explained by the independent variable.

a. If r is a negative number, then b (in the line of regression
) is negative.
true or false
b.The line of regression is use to predict the theoric average
value of y that we expect to occur when we know the value of x.
true or false
c. We can predict no matter the strength of the correlation
coefficient.
true or false
d. The set of all possible values of r is, {r: -1< r <
1
treu...

1. The dependent variable has a score in the case of logistic
regression. TRUE or FALSE and why?
2, If the probability of an even A is 0.2 and that of an event B
is 0.10 then the odds ratio is: a.1 b. 2.25 c. 2.0 d. 0.5
3. In the case of logistic regression, we estimate how much the
natural logarithm of the odds for Y =1 changes for a unit change in
X. TRUE or FALSE
4. In...

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