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27/08/2022
Assignment 11
April 12, 2018
1. A social media researcher has two variables: an independent variable “hour of day posted”
and a dependent variable “total engagement level”, which is defined as the sum of likes, shares
and comments on a post. The “individuals” in this data are individual posts. The researcher,
however, did not include the variable “content type”, which is a variable that indicates if the
post contains a picture, video or neither, in their analysis. “Content type” is related to total
engagement level. What type of variable is “content type”?
A Independent Variable
B Dependent Variable
C Lurking Variable
D Confused Variable
2. An economist would like to determine if there is a relationship between federal interest rates
and the Dow Jones Industrial Average (DJIA), on a month to month basis. That is, the
economist would like to determine if the federal interest rates cause the DJIA. What type of
variable would the federal interest rates be considered?
A Independent Variable
B Dependent Variable
C Lurking Variable
D Endogenous Variable
3. A marketer would like to explain what causes a consumer to purchase a product. She considers
using two independent variables to explain this decision: the smell in the environment and
the temperature of the environment. Smell and temperature, however, are causally related
to each other. What type of variable would “smell” therefore be considered?
A Endogenous
B Exogenous
C Confused
D Lurking
4. A financial analyst would like to determine if the previous close of the S&P 500 causes the
opening price of Apple. Both variables are numerical. Which method would most likely be
used to determine if there is a relationship?
A Comparing percentages of each category
B Converting the numerical variables to categorical
C Compare the averages across categories
D Run a Simple Linear Regression
5. Which assumption about the population refers to the fact that the individuals in the population,
when split into subgroups (where each group is determined by the possible values for
the independent variable), must have the same level of differences across all groups?
A Heterogeneity
B Homogeneity
1
C Population Size
D Equal Variances
6. If we have an independent variable that is categorical and a dependent variable that is
numerical, other than the homogeneity and heterogeneity assumptions, what also must be
true about the data of the dependent variable across different groups as determined by the
independent variable?
A The averages need to be the same.
B The standard deviations and the distributions need to be the same.
C The averages need to be different.
D The standard deviations and distributions need to be different.
7. An supply chain researcher would like to determine if there is a relationship between the
number of customers a supplier has and their performance. The number of customers, however,
is not related to any lurking variable that determines performance. The independent
variable of “number of customers” would therefore be considered
A Endogenous
B Exogenous
C Confusing
D Lurking
8. How do we determine if there is a relationship between a categorical independent variable and
a numerical dependent variable, assuming the assumptions of homogeneity and heterogeneity
hold true about our population?
A Comparing percentages of each category
B Converting the numerical variables to categorical
C Compare the averages across categories
D Run a Simple Linear Regression
9. Suppose we calculate a correlation between two numerical variables: the independent variable
being the open price of Apple, the dependent variable being the high price of Apple. Further
suppose that the correlation is 0.8. What can we say about the relationship between the
open and high price of Apple?
A There is a strong positive linear association.
B There is a weak positive linear association.
C There is a strong negative linear association.
D There is a weak negative linear association.
10. Which command in R will graph a spline plot between x1 and x2, assuming both of these
variables contain categorical data?
A spline(x1,x2)
B plot(x1,x2)
C sp(x2,x1)
D plot.spline(x1,x2)
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