WGU D491 (Introduction to Analytics) – EXAM
STUDY GUIDE 2026/2027 COMPLETE
QUESTIONS WITH VERIFIED CORRECT ANSWERS
|| 100% GUARANTEED PASS <NEWEST
VERSION>
A pharmaceutical company collected data on patient outcomes for a new drug it is testing.
Which question regarding the source or quality of the available data is most appropriate to
ask before analysis?
- Did the data come from a completely unbiased source?
- Was the data collected in secret, without the knowledge of the doctors?
- Was the data collected from electronic health records (EHRs) of patients using the drug?
- Can data be excluded to decrease the impact of side effects on the analysis?
Was the data collected from electronic health records (EHRs) of patients using the drug?
Which data source for a retail company analyzing customer behavior is an example of an
external source?
- Sales data from the company's website
- Customer demographic data from the loyalty program
- Social media activity of the company's competitors
- Employee surveys
Social media activity of the company's competitors
A data analyst is assigned to analyze sales data for a multinational retail company to identify
which products have the highest profit margins.
Which data quality requirement is most critical for this project?
- Consistency
- Completeness
,- Accuracy
- Timeliness
Accuracy
A data analyst is tasked with understanding customer satisfaction data and is emailed a file
with the data.
Which question should the data analyst ask about the data regarding where it is sourced
from?
- Is the data backed up?
- Can the data be improved?
- Has the data been copied into multiple languages?
- When was the data collected?
When was the data collected?
Which question should be asked to determine if a data set is biased?
- Is the data from a self-reported survey?
- Is the market research data too comprehensive?
- Is there too much data?
- Is the financial data objective?
Is the data from a self-reported survey?
Which technique is the most appropriate for analyzing customer demographics?
- Decision trees
- Neural network
- Clustering
- Linear regression
Clustering
Clustering is best used for customer demographics because it can group individuals or entities
based on their characteristics or behavior. This can be useful in identifying patterns or segments
within a population, which can then inform targeted marketing or outreach efforts.
What is the most appropriate analytics technique for predicting sales for the next quarter?
- Bar chart
,- Tree map
- Heat map
- Regression analysis
Regression analysis
Regression analysis is a statistical technique used to determine the relationship between a
dependent variable and one or more independent variables.
What is the most appropriate data analytics technique for analyzing website traffic patterns?
Scatterplot
Regression analysis
Line chart
Heat map
Heat map
What is the advantage of using a decision tree over a linear regression model in a data
analytics project?
Decision trees are faster and require fewer computational resources.
Decision trees can produce more accurate predictions.
Decision trees can handle missing data more effectively.
Decision trees can handle nonlinear relationships between variables.
Decision trees can handle nonlinear relationships between variables.
Decision trees can model complex, nonlinear relationships between variables, while linear
regression models are limited to linear relationships.
A retail grocer wants to use association rules in retail marketing to increase sales.
What would be the impact of using an association rule on sales data?
- By analyzing sales data, the data analyst can apply association rules to discover frequent
item sets, which are groups of items often purchased together.
- By analyzing sales data, the data analyst can apply association rules to discover stockpiling
behavior, which can be used for coupons.
- By analyzing sales data, the data analyst can apply association rules to predict revenues in
the future, which can be used in business strategy.
, - By analyzing sales data, the data analyst can apply association rules to discover rare
purchases, which can be used for future product generation.
By analyzing sales data, the data analyst can apply association rules to discover frequent item
sets, which are groups of items often purchased together.
A company wants to predict the likelihood of a customer responding to a marketing
campaign. The data set contains both numerical and categorical variables.
Which analytics technique should the company use?
Logistic regression
K-means clustering
Random forest
Principal component analysis (PCA)
Logistic regression
Logistic regression is a suitable technique for binary classification problems, such as predicting
the likelihood of a customer responding to a marketing campaign when the dataset contains
numerical and categorical variables.
An e-commerce company is interested in improving the conversion rate of its website.
In which scenario should the company's analyst use an A/B test?
- When they want to discover whether the company should move workers offshore to
decrease costs
- When they want to see whether the strategy of unique customer pricing should be used
- When they want to evaluate the market to see whether an acquisition of a smaller company
will increase market share
- When they want to find out whether changing the color of the "Add to Cart" button will
have a significant impact on sales
When they want to find out whether changing the color of the "Add to Cart" button will have a
significant impact on sales
A team working for a social media company needs to analyze customer feedback on a newly
launched product using sentiment analysis.
What is the most appropriate approach for sentiment analysis in this scenario?
Regression analysis
Text mining
STUDY GUIDE 2026/2027 COMPLETE
QUESTIONS WITH VERIFIED CORRECT ANSWERS
|| 100% GUARANTEED PASS <NEWEST
VERSION>
A pharmaceutical company collected data on patient outcomes for a new drug it is testing.
Which question regarding the source or quality of the available data is most appropriate to
ask before analysis?
- Did the data come from a completely unbiased source?
- Was the data collected in secret, without the knowledge of the doctors?
- Was the data collected from electronic health records (EHRs) of patients using the drug?
- Can data be excluded to decrease the impact of side effects on the analysis?
Was the data collected from electronic health records (EHRs) of patients using the drug?
Which data source for a retail company analyzing customer behavior is an example of an
external source?
- Sales data from the company's website
- Customer demographic data from the loyalty program
- Social media activity of the company's competitors
- Employee surveys
Social media activity of the company's competitors
A data analyst is assigned to analyze sales data for a multinational retail company to identify
which products have the highest profit margins.
Which data quality requirement is most critical for this project?
- Consistency
- Completeness
,- Accuracy
- Timeliness
Accuracy
A data analyst is tasked with understanding customer satisfaction data and is emailed a file
with the data.
Which question should the data analyst ask about the data regarding where it is sourced
from?
- Is the data backed up?
- Can the data be improved?
- Has the data been copied into multiple languages?
- When was the data collected?
When was the data collected?
Which question should be asked to determine if a data set is biased?
- Is the data from a self-reported survey?
- Is the market research data too comprehensive?
- Is there too much data?
- Is the financial data objective?
Is the data from a self-reported survey?
Which technique is the most appropriate for analyzing customer demographics?
- Decision trees
- Neural network
- Clustering
- Linear regression
Clustering
Clustering is best used for customer demographics because it can group individuals or entities
based on their characteristics or behavior. This can be useful in identifying patterns or segments
within a population, which can then inform targeted marketing or outreach efforts.
What is the most appropriate analytics technique for predicting sales for the next quarter?
- Bar chart
,- Tree map
- Heat map
- Regression analysis
Regression analysis
Regression analysis is a statistical technique used to determine the relationship between a
dependent variable and one or more independent variables.
What is the most appropriate data analytics technique for analyzing website traffic patterns?
Scatterplot
Regression analysis
Line chart
Heat map
Heat map
What is the advantage of using a decision tree over a linear regression model in a data
analytics project?
Decision trees are faster and require fewer computational resources.
Decision trees can produce more accurate predictions.
Decision trees can handle missing data more effectively.
Decision trees can handle nonlinear relationships between variables.
Decision trees can handle nonlinear relationships between variables.
Decision trees can model complex, nonlinear relationships between variables, while linear
regression models are limited to linear relationships.
A retail grocer wants to use association rules in retail marketing to increase sales.
What would be the impact of using an association rule on sales data?
- By analyzing sales data, the data analyst can apply association rules to discover frequent
item sets, which are groups of items often purchased together.
- By analyzing sales data, the data analyst can apply association rules to discover stockpiling
behavior, which can be used for coupons.
- By analyzing sales data, the data analyst can apply association rules to predict revenues in
the future, which can be used in business strategy.
, - By analyzing sales data, the data analyst can apply association rules to discover rare
purchases, which can be used for future product generation.
By analyzing sales data, the data analyst can apply association rules to discover frequent item
sets, which are groups of items often purchased together.
A company wants to predict the likelihood of a customer responding to a marketing
campaign. The data set contains both numerical and categorical variables.
Which analytics technique should the company use?
Logistic regression
K-means clustering
Random forest
Principal component analysis (PCA)
Logistic regression
Logistic regression is a suitable technique for binary classification problems, such as predicting
the likelihood of a customer responding to a marketing campaign when the dataset contains
numerical and categorical variables.
An e-commerce company is interested in improving the conversion rate of its website.
In which scenario should the company's analyst use an A/B test?
- When they want to discover whether the company should move workers offshore to
decrease costs
- When they want to see whether the strategy of unique customer pricing should be used
- When they want to evaluate the market to see whether an acquisition of a smaller company
will increase market share
- When they want to find out whether changing the color of the "Add to Cart" button will
have a significant impact on sales
When they want to find out whether changing the color of the "Add to Cart" button will have a
significant impact on sales
A team working for a social media company needs to analyze customer feedback on a newly
launched product using sentiment analysis.
What is the most appropriate approach for sentiment analysis in this scenario?
Regression analysis
Text mining
