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Return to Research Methods Using R 1e Student Resources
Chapter 4 Multiple choice questions
Quiz Content
*
not completed
.
Create a data object containing the following numbers:
-9, 32, 1, -7, 25, 12, 4, 16
Use the t.test function to run a one sample t-test comparing the mean of these numbers to 0. What is the t-value?
t = 0.12
correct
incorrect
t = 1.78
correct
incorrect
t = 3.5
correct
incorrect
t = 1.4
correct
incorrect
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not completed
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We can raise numbers to a power using the ^ symbol. So 2^2 means 2 squared, which returns the answer 4. You can also raise data objects to a power in the same way.
Using the values from question 1, conduct paired and unpaired t-tests to compare them with their squared values. Which answer best describes the outcome?
Both paired and unpaired tests were significant, but the paired test had a larger t-value
correct
incorrect
Both paired and unpaired tests were significant, but the unpaired test had a larger t-value
correct
incorrect
Neither the paired nor the unpaired test was significant
correct
incorrect
The paired test was significant, but the unpaired test was not
correct
incorrect
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not completed
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Create a second data object as follows:
b <- c(13, -31, -1, -4, -26, 11, 0, 4)
What is the correlation between these numbers and the values from the question 1?
R = -0.74
correct
incorrect
R = 0.74
correct
incorrect
R = 0.11
correct
incorrect
R = -0.11
correct
incorrect
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not completed
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Now use the cor.test function to assess whether the correlation is significant. What is the p-value?
p
= 0.33
correct
incorrect
p
= 0.15
correct
incorrect
p
= 0.01
correct
incorrect
p
= 0.04
correct
incorrect
*
not completed
.
Download the data file for the multiple-choice questions for Chapter 4
, and open it in
R.
Use the
lm
function to run a linear regression on the data in the
regdata
object, using the formula: DV ~ IV
What is the Adjusted R
^{2}
value for the regression?
0.26
correct
incorrect
0.29
correct
incorrect
0.99
correct
incorrect
0.002
correct
incorrect
*
not completed
.
Run a one way independent ANOVA on the data stored in
AOVdata
. The dependent variable is called
RT
, and the independent variable is called
attentioncondition
. What is the value of the F-ratio?
0.04
correct
incorrect
40.3
correct
incorrect
5.51
correct
incorrect
3.53
correct
incorrect
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not completed
.
Rerun the analysis from Question 6 as a linear regression model using the lm function. What is the p-value for the slope linking levels 1 and 2 of the independent variable?
<2*10
^{-16}
correct
incorrect
0.207
correct
incorrect
0.013
correct
incorrect
0.043
correct
incorrect
*
not completed
.
Calculate a paired samples t-test using the data stored in
paireddata
. What is the p-value for the difference in stickiness between conditions 1 and 2?
0.44
correct
incorrect
0.28
correct
incorrect
0.79
correct
incorrect
0.11
correct
incorrect
*
not completed
.
Use the formula in Table 4.1 to calculate a one-way repeated measures ANOVA using the data in
rmdata
. What is the F-ratio for the effect of condition on the dependent variable
cellsize
, and is this significant at
p
<0.05?
F = 57.99, significant at
p
<0.05
correct
incorrect
F = 57.99, not significant at
p
<0.05
correct
incorrect
F = 29.76, significant at
p
<0.05
correct
incorrect
F = 29.76, not significant at
p
<0.05
correct
incorrect
*
not completed
.
Run a 2x2 factorial independent ANOVA on the data stored in
factdata
, to see how the independent variables IV1 and IV2 influence the dependent variable DV. Which summary best describes the results?
Both independent variables have a significant effect, and the interaction is also significant
correct
incorrect
Both independent variables have a significant effect, but the interaction is not significant
correct
incorrect
IV1 has a significant effect, but IV2 does not, and there is no interaction
correct
incorrect
Neither IV has a significant effect, but the interaction between them is significant
correct
incorrect
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