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R-Matey -- Exam #2 Review

Total questions: 21

Worksheet time: 11mins

Name
Class
Date
1.

Which one of the following commands does not allow descriptives to be generated by group?

a)

by()

b)

aggregate()

c)

with()

d)

All answers generate descriptives

2.

Which of the following packages provides graphing functions that allow "conditioning" on one or more factors?

a)

lattice package

b)

car package

c)

psych package

d)

None of these are correct

3.

The formula syntax uses the (fill in the blank) to separate the response variables on the left from the explanatory variables on the right

a)

|

b)

:

c)

~

d)

None of these answers are correct

4.

The default when using the histogram() function is a graph of the (fill in the blank) within in each group.

a)

Counts

b)

Proportions

c)

Frequencies

d)

None of the answers are correct

5.

The histogram() function allows you to condition on (fill in the blank) factor(s).

a)

one

b)

two

c)

three

d)

all of these are correct

6.

"Conditioning" is indicated with which one of the following symbols?

a)

~

b)

$

c)

|

d)

%

7.

The bwplot() from the lattice package is similiar to boxplot() except that it also allows you to (fill in the blank).

a)

condition on factors

b)

plot additional deciles

c)

extrapolate

d)

none of these answers are correct

8.

If you wanted to test whether group size varied between groups, you could run which of the following statistical tests?

a)

F-test

b)

t-test

c)

chi-squared test

d)

none of these are correct

9.

Statistical tests help us to identify (fill in the blank) differences not due to minor variation in the data

a)

uncertain

b)

real

c)

imaginary

d)

none of these are correct

10.

A t-test will test which of the following for statistical significance?

a)

Comparing the standard deviations between exactly 2 groups

b)

Comparing the medians between exactly 2 groups

c)

Comparing the means between exactly 2 groups

d)

None of these answers are correct

11.

Many statistical tests assume that the data follows a (fill in the blank) distribution.

a)

normal

b)

uniform

c)

exponential

d)

all of these are correct

12.

To test the statistical differences between 3 or more means you can use which of the following tests?

a)

t-test

b)

Z-test

c)

ANOVA

d)

All of these answers are correct

13.

In order for ANOVA to test which model is better, the models must be (fill in the blank).

a)

the same size

b)

nested

c)

repeatable

d)

none of these are correct

14.

In linear modeling, the model outcome is also called the (fill in the blank).

a)

explanatory variable

b)

response or dependent variable

c)

independent variable

d)

all of these are correct

15.

A driver, in a key driver analysis, only implies which of the following?

a)

causation

b)

association

c)

similarity

d)

none of these are correct

16.

Which of the following are alternative names for linear modelling?

a)

Regression analysis

b)

Linear regression analysis

c)

Least squares fitting

d)

All of these are alternative names

17.

Which of the following is not a step in the linear modeling process

a)

Inspecting your data

b)

Transforming your data

c)

Checking relationships between the variables

d)

All of the above are steps

18.

Checking correlation between the variables prior to linear modeling is an important step. Which of the following might trigger concern?

a)

r>0.5

b)

r<0.6

c)

r>0.9

d)

r<0.3

19.

Which for the following is a true statement in comes to the development of linear models?

a)

Residual values should be normally distributed

b)

Skewed data is fine for use in developing linear models

c)

The optimal model maximizes the distances between the line and the data points

d)

Data should be standardized before being transformed

20.

Which function graphs the 95% confidence intervals for the all of the estimated model coefficients for sat.model?

a)

plot(sat.model)

b)

coefplot(sat.model)

c)

bwplot(sat.model)

d)

all of these will work

21.

Which is false about the R-squared value calculated for a given linear model?

a)

It measures the amount of variation explained by the model

b)

It will never be smaller then the Adjusted R-squared value

c)

It is unrelated to correlation

d)

None of the above these are false