BSAN 160 Exam Review Questions
and Answers
Which of the below is a method to deal with filling out the missing values in data?
data cleaning
data reduction
data smoothing
data imputation - Answer-data imputations
Which of the below statement(s) is/are correct?
A: An important data transformation subtask is to select the relevant data using domain
expert input, i.e., decide which sources and data to collect.
B: When merging two data source tables A and B, using the full outer join method
eliminates all rows from the resulting table that do not have corresponding rows in both
source tables A and B.
C: For numerical variables, normalizing the observed values between two values, such
as 0 and 1, allows to rescale the values and compare variables with different means
and/or standard deviations on a single scale.
D: Identifying and reducing noise in the data is a subtask of data reduction. - Answer-C
When analyzing the original data of household income of a selected population,
analysts notice that 5% of observations are missing and entered in the dataset as N/A
(not available). Further, they notice that there are a few extremely low household
income values. Which of the following method(s) would be well-suited to prepare the
data before conducting descriptive analysis, such as calculating descriptive statistics
and creating histogram of household income?
A: Use the original dataset to avoid introducing additional noise to data prior to analysis
B: Identify the outliers in data with statistical techniques and remove the extremely low
income values
C: Identify the outliers in data with statistical techniques and replace the extremely low
values using the mean of the income values to smooth the values
D: Fill in missing values (imputations) with most appropriate values using zeros to
indicate that these income valu - Answer-B and C
Which of the below statement(s) is/are correct?
A: Information dashboards provide interactive visual displays of important information
that is so that the level of granularity of key insights can modified by drilled in or moving
out for more / less exploration
B: Visual analytics combines data visualization and different analytics methods such as
descriptive, predictive and prescriptive analytics.
C: Interactive information dashboards provide key insights as static information that
focus on better understanding of what happened. - Answer-A and B
, Which of the following data preprocessing activity/activities that Mia conducts would fall
under data transformation?
A: Identify and replace extremely high and low selling price values using appropriate
imputation methods
B: Convert number of bikes sold per month (numeric) into discrete categories using
frequency-based bins
C: Filter the data to ensure that only key performance and price features needed for the
analysis are included in the data
D: Reduce the range of values of quarterly market share (numeric) data to a standard
range (e.g., 0 to 1 or -1 to +1) by using normalization or scaling techniques
E: Oversample the less represented financial performance measurements - Answer-B
and D
Which chart should Mia use to visualize the relative proportion of market share of
Peloton in 2020 compared to its competitors Nordic Track, Myx Fitness, and Echelon? -
Answer-Pie chart
Which chart should Mia use to visualize the number of new members joining the
Peloton customer community every month from 2012 to 2020? - Answer-Line chart
Which of the following data preprocessing activity that Mia conducts is not associated
with data cleaning? - Answer-Derive a new variable representing total time of class
material from existing variables
Mia decides to use imputation methods as part of the data preprocessing. What is the
main purpose of imputation methods? - Answer-Fill in missing values with most
appropriate values
T or F Linear regression models represent the mathematical relationship between one
or more dependent variables to explain or predict a binary (i.e., a variable that takes
values 0=no and 1=yes) independent variable." - Answer-False
T or F: "Linear regression analysis can be used to predict an unknown value of a
dependent variable using the values of a set of numeric and/or categorical independent
variables." - Answer-True
Comparing two regression models (Model 1 and Model 2) developed using the same
dataset, assume Model 1 has an R-squared of 0.58 and Model 2 has an R-squared of
0.79. Which of the following statement(s) is/are correct?
A: Model 2 describes 79% of the variation in the given data
B: Comparing both models and how well they explain the variation in the given data,
Model 1 is a better fit compared to Model 2
C: The independent variables used in Model 1 do not capture 42% of the variation in the
given data - Answer-A and C
and Answers
Which of the below is a method to deal with filling out the missing values in data?
data cleaning
data reduction
data smoothing
data imputation - Answer-data imputations
Which of the below statement(s) is/are correct?
A: An important data transformation subtask is to select the relevant data using domain
expert input, i.e., decide which sources and data to collect.
B: When merging two data source tables A and B, using the full outer join method
eliminates all rows from the resulting table that do not have corresponding rows in both
source tables A and B.
C: For numerical variables, normalizing the observed values between two values, such
as 0 and 1, allows to rescale the values and compare variables with different means
and/or standard deviations on a single scale.
D: Identifying and reducing noise in the data is a subtask of data reduction. - Answer-C
When analyzing the original data of household income of a selected population,
analysts notice that 5% of observations are missing and entered in the dataset as N/A
(not available). Further, they notice that there are a few extremely low household
income values. Which of the following method(s) would be well-suited to prepare the
data before conducting descriptive analysis, such as calculating descriptive statistics
and creating histogram of household income?
A: Use the original dataset to avoid introducing additional noise to data prior to analysis
B: Identify the outliers in data with statistical techniques and remove the extremely low
income values
C: Identify the outliers in data with statistical techniques and replace the extremely low
values using the mean of the income values to smooth the values
D: Fill in missing values (imputations) with most appropriate values using zeros to
indicate that these income valu - Answer-B and C
Which of the below statement(s) is/are correct?
A: Information dashboards provide interactive visual displays of important information
that is so that the level of granularity of key insights can modified by drilled in or moving
out for more / less exploration
B: Visual analytics combines data visualization and different analytics methods such as
descriptive, predictive and prescriptive analytics.
C: Interactive information dashboards provide key insights as static information that
focus on better understanding of what happened. - Answer-A and B
, Which of the following data preprocessing activity/activities that Mia conducts would fall
under data transformation?
A: Identify and replace extremely high and low selling price values using appropriate
imputation methods
B: Convert number of bikes sold per month (numeric) into discrete categories using
frequency-based bins
C: Filter the data to ensure that only key performance and price features needed for the
analysis are included in the data
D: Reduce the range of values of quarterly market share (numeric) data to a standard
range (e.g., 0 to 1 or -1 to +1) by using normalization or scaling techniques
E: Oversample the less represented financial performance measurements - Answer-B
and D
Which chart should Mia use to visualize the relative proportion of market share of
Peloton in 2020 compared to its competitors Nordic Track, Myx Fitness, and Echelon? -
Answer-Pie chart
Which chart should Mia use to visualize the number of new members joining the
Peloton customer community every month from 2012 to 2020? - Answer-Line chart
Which of the following data preprocessing activity that Mia conducts is not associated
with data cleaning? - Answer-Derive a new variable representing total time of class
material from existing variables
Mia decides to use imputation methods as part of the data preprocessing. What is the
main purpose of imputation methods? - Answer-Fill in missing values with most
appropriate values
T or F Linear regression models represent the mathematical relationship between one
or more dependent variables to explain or predict a binary (i.e., a variable that takes
values 0=no and 1=yes) independent variable." - Answer-False
T or F: "Linear regression analysis can be used to predict an unknown value of a
dependent variable using the values of a set of numeric and/or categorical independent
variables." - Answer-True
Comparing two regression models (Model 1 and Model 2) developed using the same
dataset, assume Model 1 has an R-squared of 0.58 and Model 2 has an R-squared of
0.79. Which of the following statement(s) is/are correct?
A: Model 2 describes 79% of the variation in the given data
B: Comparing both models and how well they explain the variation in the given data,
Model 1 is a better fit compared to Model 2
C: The independent variables used in Model 1 do not capture 42% of the variation in the
given data - Answer-A and C
