Question 1

Presenting an assessment of variables of interest against a given benchmark for a company is an example of what data presentation format?
A) Query
B) Scorecard
C) KPIs (key performance indicators)
D) Dashboard

Accepted Answer

A scorecard is a data presentation format used to present an assessment of variables of interest against a given benchmark for a company or organization. It provides a visual representation of how well the company is performing against its goals and objectives. KPIs and dashboards are also often used in conjunction with scorecards to provide additional insight and context. However, neither of the options A, C, or D explicitly refers to a scorecard.

Question 2

In describing the data-generating process for "click-throughs" for one of your firm's advertising campaigns you've assumed the following relationship: Y_i = f (H_i, J_i) + U_i, where Y_iis if individual i clicked through, H_i is individual i's household income, J_i is an indicator for whether or not individual i has a job. What type of factors might be contained in U_i? A) A factor that affects J_i but does not affect Y_i. B) A factor that affects H_i but does not affect Y_i. C) A factor that affects H_i and Y_i. D) None of the answers is correct.

Accepted Answer

The variables H_i and J_i are already accounted for in the model as predictors of Y_i. Therefore, any additional factors contained in U_i must affect Y_i but not be accounted for by H_i or J_i. Therefore, option C is the correct answer as U_i could contain variables that affect both household income and click-throughs.

Question 3

Quantitative measures meant to summarize and interpret properties of a dataset are instances of:
A) pivot tables.
B) descriptive statistics.
C) linear regressions.
D) outliers.

Accepted Answer

Descriptive statistics are the measures used to summarize and interpret the properties of a dataset. Pivot tables are a tool for organizing and summarizing data, but they are not a quantitative measure. Linear regression is a statistical technique used to study the relationship between two variables, but it is not a measure of the dataset itself. Outliers are data points that fall far outside the normal range of values, but they are not a measure that summarizes the dataset.

Question 4

If commercial real estate costs of Kroger affect demand for Kroger Milk through the product prices Kroger charges to its customers, this is an example of what type of relationship?
A) A direct causal effect of real estate costs on product demand
B) An indirect causal effect of product prices on product demand
C) An indirect causal effect of product demand on product prices
D) An indirect causal effect of real estate costs on product demand

Accepted Answer

Commercial real estate costs are not directly related to the demand for Kroger Milk, but they indirectly affect it through the prices Kroger charges for the product, which may be influenced by real estate costs. Therefore, this is an example of an indirect causal effect of real estate costs on product demand.

Question 5

Measures of the central tendencies of variables such as the mean, median, and mode are examples of:
A) descriptive statistics.
B) data mining.
C) covariance.
D) causal relationships

Accepted Answer

Measures of central tendencies (mean, median, mode) are used in descriptive statistics to summarize and describe the main features of a dataset. Descriptive statistics are used to organize, summarize and describe the characteristics of a sample or population. Therefore, choice A is the correct option.

Question 6

Use the following dataset to answer the following question. $$\begin{array} { | c | c | c | c | c |} 
\hline \text { State } & \text { Year } & \text { Sales } & \text { Capital Expenditures } & \text { Wages } \
\hline \text { Westerm } & 2016 & \$ 750,000 & \$ 130,000 & \$ 330,000 \
\hline \text { Eartem1 } & 2016 & \$ 645,000 & \$ 225,000 & \$ 430,000 \
\hline \text { Westerm } & 2017 & \$ 770,050 & \$ 145,000 & \$ 230,000 \
\hline \text { Eartern } & 2017 & \$ 925,000 & \$ 125,000 & \$ 530,000 \
\hline
\end{array}$$ Using a spreadsheet software, such as Excel, to preview different views of this dataset, such as Sales in the Eastern part of the country, would be aided by what?
A) Linear regression
B) Cluster analysis
C) Pivot table
D) Scorecard

Accepted Answer

Pivot tables can help organize and summarize large amounts of data, allowing for easier analysis and comparison of different variables. In this case, a pivot table could be used to easily filter and view sales data for only the Eastern states. Linear regression, cluster analysis, and scorecards may also be useful for analyzing this dataset, but they are not as directly relevant to the specific question being asked.

Question 7

Suppose you collect monthly sales figures for each store location in your company as well as the wages paid to employees for each store, and that you have a complete history for the last ten years for each store. What is the type of this data set?
A) Pooled cross-section
B) Unstructured data
C) Censored data
D) Panel

Accepted Answer

This data set is a panel, as it includes data collected over time for each store location.

Question 8

The process of identifying distinctive relationships between observations in a data set, or pattern discovery, within a very large dataset is typically known as?
A) Data mining
B) Outlier detection
C) Query
D) Pattern discovery

Accepted Answer

The process described in the question is commonly referred to as data mining. This involves analyzing large sets of data to discover patterns, relationships, and trends. Outlier detection involves identifying data points that deviate significantly from the rest of the dataset, while a query is a specific request for information from a database. Pattern discovery is another term for data mining.

Question 9

Any request for information from a database is an example of:
A) pattern discovery.
B) data mining.
C) query.
D) association analysis.

Accepted Answer

A request for information from a database is typically referred to as a query. Pattern discovery, data mining, and association analysis all involve analyzing data in a more complex manner than simply requesting information.

Question 10

In grouping customers into separate types according to their spending, internet browsing, payment method, and age a firm is engaging in what sort of analysis?
A) Data mining
B) Cluster analysis
C) Outlier detection
D) Linear regression

Accepted Answer

The firm is engaging in cluster analysis, which is a technique of grouping data points into clusters based on similarities and differences between them. In this case, the firm is using different variables such as spending, internet browsing, payment method, and age to group customers into separate types. Data mining is a broader term that refers to the process of extracting information and insights from large datasets, while outlier detection and linear regression are other types of data analysis techniques.

Question 11

In examining the career earnings of different undergraduate majors, identifying Michael Jordan as an atypical instance amongst Geography majors would be an example of what sort of data analysis?
A) Dashboard
B) Pattern discovery
C) Outlier detection
D) Data mining

Accepted Answer

Outlier detection is the process of identifying values that lie far outside the expected range of values in a dataset. Michael Jordan's exceptional career earnings as a Geography major would qualify as an outlier in this analysis. A dashboard would provide an overview of multiple metrics in a single interface, pattern discovery involves identifying trends and relationships in data, and data mining involves exploring and analyzing large datasets for insights.

Question 12

Identifying distinctive relationships between observations in a dataset is an example of what sort of data analysis?
A) Query
B) Pattern discovery
C) Mean
D) Covariance

Accepted Answer

Identifying distinctive relationships between observations in a dataset is an example of pattern discovery, which involves finding patterns, clusters, or anomalies in the data that may not be immediately apparent. This type of analysis can be used for various applications such as market segmentation, fraud detection, or customer behavior analysis. The other choices (A, C, D) are not related to identifying relationships between observations.

Question 13

Suppose you've assumed the following two data-generating processes: (1) Y_i = f (H_i, J_i) and (2) J_i = g (X_i, Z_i). What do these assumptions imply? A) J has a direct causal effect on H. B) Z has a direct causal effect on Y. C) X has an indirect causal effect on J. D) Z has an indirect causal effect on Y.

Accepted Answer

The assumptions imply that Z affects J through the function g, and J affects Y through the function f, creating an indirect causal path from Z to Y.

Question 14

In grouping TV markets into separate types according to regional spending, demographics, and business activity, and cost of advertising is engaging in what sort of analysis?
A) Passive prediction
B) Cluster analysis
C) Data mining
D) Linear regression

Accepted Answer

Cluster analysis is a statistical technique used to group similar objects or regions that have something in common. In this case, the TV markets are being grouped according to regional spending, demographics, and business activity, and cost of advertising.

Question 15

Which of the following would not be an example of summary statistic of a variable within dataset?
A) Mean
B) Variance
C) Interquartile range
D) None of the above.

Accepted Answer

All of the options given (mean, variance, and interquartile range) are examples of summary statistics of a variable within a dataset, so none of them would be excluded. Therefore, the answer is D.

Question 16

Providing a graphical presentation of past trends of a set of critical indicators for a company is an example of what data presentation format?
A) Query
B) Report
C) KPIs (key performance indicators)
D) Dashboard

Accepted Answer

This is an example of a dashboard, which provides a visual snapshot of a company's critical indicators in a easily understandable format. A report could also work, but a dashboard is specifically designed for providing a quick and easy overview of key performance indicators. A query is a request for specific data, and KPIs are the actual critical indicators being presented.

Question 17

Use the following presentation to answer the following question. $$\begin{array} { | c | c | c | c | c | } 
\hline \text { State } & \text { Year } & \text { Salesper Stare } & \text { Target } & \text { Perfarmance } \
\hline \text { Western } & 2016 & \$ 750,000 & \$ 700,000 & \text { Good } \
\hline \text { Eastern } & 2016 & \$ 645,000 & \$ 680,000 & \text { Nearing Acceptable } \
\hline \text { Western } & 2017 & \$ 770,050 & \$ 745,000 & \text { Good } \
\hline \text { Eastern } & 2017 & \$ 925,000 & \$ 825,000 & \text { Good } \
\hline
\end{array}$$ This presentation is an example of what?
A) Cluster analysis
B) Association analysis
C) Pivot table
D) Scorecard

Accepted Answer

This presentation is a scorecard, which is a tool used to monitor and track progress towards specific goals or targets. It includes information such as the state, year, sales, target, and performance, which are all common components of a scorecard. Cluster analysis, association analysis, and pivot tables are all different types of data analysis techniques that are not specifically related to scorecards.

Question 18

In examining the career earnings of individuals with different levels of college/graduate attainment, identifying Bill Gates as an atypical instance amongst the population with less than a bachelor's degree, would be an example of what sort of data analysis?
A) Query
B) Pattern discovery
C) Data mining
D) Outlier detection

Accepted Answer

Identifying Bill Gates as an atypical instance amongst the population with less than a bachelor's degree is an example of outlier detection, as he is a significant deviation from what is expected in that group.

Question 19

Use the following dataset to answer the following question. $$\begin{array} { | l | c | c | c | c | } 
\hline { \text { Name } } & \text { Year } & \text { Salary } & \text { Tenure } & \text { MBA? } \
\hline \text { Drritry Haas } & 2017 & \$ 98,000 & 5 \text { years } & \text { Y } \
\hline \text { Jackie Bay } & 2017 & \$ 83,000 & 3 \text { years } & \mathrm { N } \
\hline \text { Renee Topkis } & 2017 & \$ 77,000 & 12 \text { years } & \mathrm { Y } \
\hline \text { Maria Val } & 2017 & \$ 79,000 & \text { 8years } & \mathrm { N } \
\hline
\end{array}$$
- What is the type of data set?
A) Pooled cross-section
B) Panel
C) Unstructured
D) Cross-section

Accepted Answer

The dataset is a cross-section because it contains data on multiple subjects (individuals) at a single point in time (the year 2017), without tracking these subjects over multiple time periods.

Question 20

If advertising exposure, disposable income and price affect demand for a product, and advertising exposure affects the price of the product, what type of relationship is not present?
A) A direct causal effect of advertising exposure on product demand
B) A direct causal effect of advertising exposure on product prices
C) An indirect causal effect of disposable income on product demand
D) A direct causal effect of product prices on product demand

Accepted Answer

Disposable income's effect on product demand is described as direct, not indirect, because the question does not mention any mediator between disposable income and product demand.

Quiz 1: The Roles of Data and Predictive Analytics in Business

Presenting an assessment of variables of interest against a given benchmark for a company is an example of what data presentation format?

Quantitative measures meant to summarize and interpret properties of a dataset are instances of:

If commercial real estate costs of Kroger affect demand for Kroger Milk through the product prices Kroger charges to its customers, this is an example of what type of relationship?

Measures of the central tendencies of variables such as the mean, median, and mode are examples of:

Suppose you collect monthly sales figures for each store location in your company as well as the wages paid to employees for each store, and that you have a complete history for the last ten years for each store. What is the type of this data set?

The process of identifying distinctive relationships between observations in a data set, or pattern discovery, within a very large dataset is typically known as?

Any request for information from a database is an example of:

In grouping customers into separate types according to their spending, internet browsing, payment method, and age a firm is engaging in what sort of analysis?

In examining the career earnings of different undergraduate majors, identifying Michael Jordan as an atypical instance amongst Geography majors would be an example of what sort of data analysis?

Identifying distinctive relationships between observations in a dataset is an example of what sort of data analysis?

Suppose you've assumed the following two data-generating processes: (1) Y_i = f (H_i, J_i) and (2) J_i = g (X_i, Z_i) . What do these assumptions imply?

In grouping TV markets into separate types according to regional spending, demographics, and business activity, and cost of advertising is engaging in what sort of analysis?

Which of the following would not be an example of summary statistic of a variable within dataset?

Providing a graphical presentation of past trends of a set of critical indicators for a company is an example of what data presentation format?

In examining the career earnings of individuals with different levels of college/graduate attainment, identifying Bill Gates as an atypical instance amongst the population with less than a bachelor's degree, would be an example of what sort of data analysis?

If advertising exposure, disposable income and price affect demand for a product, and advertising exposure affects the price of the product, what type of relationship is not present?