Question 1

Which of the following is NOT a process of the data management system?
A) acquire
B) distribute
C) store
D) summarize

Accepted Answer

Summarize is not considered a core process of the data management system. Data management typically involves acquiring, distributing, and storing data. Summarizing data, while important for analysis and reporting, is not a primary process of managing the data itself but rather a way to interpret or analyze the data after it has been managed.

Question 2

Which term represents data items, events, or things stored in a database file?
A) instance
B) entity
C) settings
D) quantitative

Accepted Answer

An entity represents data items, events, or things stored in a database file. It is a fundamental concept in database design, representing real-world objects or concepts that have data stored about them.

Question 3

Mary in the accounting department has been assigned a specific vehicle as her company car to perform audits. This represents which type of relationship?
A) 1 : 1
B) 1 : M
C) M : N
D) M : M

Accepted Answer

Mary is assigned a specific vehicle, indicating a one-to-one (1:1) relationship between her and the company car.

Question 4

Select, From, and Where keywords are statements used in __________.
A) DBMS
B) XML
C) SQL
D) JAVA

Accepted Answer

The Select, From, and Where keywords are fundamental components of SQL (Structured Query Language), which is used for managing and manipulating relational databases.

Question 5

The primary purpose of a(n) _____________ is to support decision-making and provide a composite view of the organization.
A) data warehouse
B) data mart
C) entity
D) attribute

Accepted Answer

A data warehouse is designed to support decision-making processes by consolidating data from various sources into a single, comprehensive database, allowing for a unified view of the organization. This facilitates analysis and reporting across different segments of the business.

Question 6

A non-relational database structure that can support the storage of a wide ranges of data, including structured, semi-structured, and unstructured is called ___________.
A) SQL
B) Free Range
C) NoSQL
D) Recreational

Accepted Answer

NoSQL databases are designed to handle a wide variety of data types, including structured, semi-structured, and unstructured data, making them suitable for big data and real-time web applications.

Question 7

Mary has been tasked with reviewing a large data file. She wants to begin by first inspecting the number of values in each cell, both numeric and non-numeric, for any blank entries. The plan is to first find the blank or missing values for first review. Using Excel, what function(s) should she use to complete this task?
A) COUNT
B) COUNTA
C) COUNTIF
D) Both COUNT and COUNTA

Accepted Answer

The answer of Mary has been tasked with reviewing a...

Question 8

Molly wants to view observations with missing values in Inventory. However, her data set is quite large. What functions should she use to complete her task in R?
A) > is.na (myData.Inventory)
B) > is.na (myData$Inventory)
C) > which (is.na(myData$Inventory))
D) > which (is.na(myData.Inventory))

Accepted Answer

The which() function returns the indices of the elements in a vector that meet a specified condition. In this case, the condition is that the element is NA. The is.na() function returns a logical vector indicating which elements of a vector are NA. So, the which(is.na(myData$Inventory)) expression will return the indices of the elements in the Inventory column of the myData data frame that are NA.

Question 9

In the presence of outliers in a data set, extremely small or large values, it is preferred to use the __________ instead of the ________ to impute missing variables.
A) median; mean
B) mean; median
C) subset; total
D) average; range

Accepted Answer

The median is less sensitive to outliers than the mean, making it a better choice for imputing missing values in a dataset with extreme values.

Question 10

In a data set with 18 variables, if 11% of the values, randomly spread across observations, are missing (blank), what is the probable percent of complete and usable observations?
A) 89%
B) 11%
C) 12.27%
D) 7.70%

Accepted Answer

Given that 11% of values are missing randomly across observations in a dataset with 18 variables, the probability of an observation being complete (i.e., having no missing values) is (1 - 0.11)^18, as each of the 18 variables has an 89% chance of being present. Calculating this gives approximately 0.1227 or 12.27%, indicating that about 12.27% of observations are likely to be complete and usable.

Question 11

In a data set with 20 variables, if 8% of the values, randomly spread across observations, are missing (blank), what is the probable percent of complete and usable observations?
A) 92%
B) 8%
C) 18.87%
D) 15.29%

Accepted Answer

Given that 8% of the values are missing randomly across observations in a dataset with 20 variables, the probability of an observation being complete (i.e., having no missing values) is (1 - 0.08)^20. This is because each of the 20 values in an observation has a 92% chance of being present (100% - 8% missing = 92% present). Calculating this gives a probability of approximately 0.8187 or 81.87% for each value being present. However, for an observation to be complete, all 20 values must be present, which significantly lowers the probability of an observation being complete. The correct calculation for the percentage of complete observations is 1 - 0.8187 = 0.1887 or 18.87%, indicating that only about 18.87% of observations are likely to be complete and usable.

Question 12

Using the simple mean imputation strategy, what value would be placed in the missing observation in x₁? A) 18 B) 82 C) 80 D) 66

Accepted Answer

The answer of Using the simple mean imputation strategy, what...

Question 13

Using the simple mean imputation strategy, what value would be placed in the missing observation in x₁? A) 17 B) 84 C) 83 D) 90

Accepted Answer

The answer of Using the simple mean imputation strategy, what...

Question 14

Using the omission strategy, what value would be placed in the missing observation in x₁? A) No value because excluded B) 87 C) 85 D) 69

Accepted Answer

The answer of Using the omission strategy, what value would...

Question 15

Using the omission strategy, what value would be placed in the missing observation in x₁? A) No value because excluded B) 84 C) 83 D) 90

Accepted Answer

The answer of Using the omission strategy, what value would...

Question 16

When performing an analysis, one technique is called RFM. Which of the following is not reflective of RFM?
A) recency
B) frequency
C) monetary
D) relevancy

Accepted Answer

RFM stands for Recency, Frequency, and Monetary value, which are key customer segmentation criteria. "Relevancy" is not part of the RFM model.

Question 17

Mark wants to have a better understanding of his client base at the credit union. To do so, he is running a report to show loan amount approval with corresponding credit scores. He realized the data set is quite large and wants to create categories by grouping. To do this, he needs to do all the following except
A) identify the value he wants to transform into smaller groups or bins.
B) remove 20% of the data to create a training set.
C) ensure the data sets are not overlapping.
D) identify how he wants the observations to be labeled in the bin.

Accepted Answer

Removing 20% of the data to create a training set is not necessary for the process of categorizing or binning data. This step is more relevant to machine learning model training rather than categorizing data for analysis.

Question 18

In Analytic Solver, Aimee is trying to create a new column called RFM. This column is merging multiple values into one cell. The function to accomplish this is called?
A) TRANSFORM
B) CONCATENATE
C) VARIABLE
D) VLOOKUP

Accepted Answer

The CONCATENATE function is used to merge multiple values into one cell, which is what Aimee is trying to accomplish by creating a new column called RFM in Analytic Solver.

Question 19

The function that provides a natural logarithm in Excel is?
A) The INT function
B) The LN function
C) The YEARFRAC function
D) The VLOOKUP function

Accepted Answer

The LN function in Excel is used to calculate the natural logarithm of a number.

Question 20

In R, Mary wants to understand the number of days between rain events in Chicago, IL. What function is used to find the number of rain events between today and January 1, 2019?
A) difftime
B) as.numeric
C) diffdate
D) floor

Accepted Answer

The `difftime` function in R calculates the difference in time between two dates, which can be used to understand the number of days between events, such as rain events.

Quiz 2: Data Management and Wrangling

Which of the following is NOT a process of the data management system?

Which term represents data items, events, or things stored in a database file?

Mary in the accounting department has been assigned a specific vehicle as her company car to perform audits. This represents which type of relationship?

Select, From, and Where keywords are statements used in __________.

The primary purpose of a(n) _____________ is to support decision-making and provide a composite view of the organization.

A non-relational database structure that can support the storage of a wide ranges of data, including structured, semi-structured, and unstructured is called ___________.

Molly wants to view observations with missing values in Inventory. However, her data set is quite large. What functions should she use to complete her task in R?

In the presence of outliers in a data set, extremely small or large values, it is preferred to use the __ instead of the to impute missing variables.

In a data set with 18 variables, if 11% of the values, randomly spread across observations, are missing (blank) , what is the probable percent of complete and usable observations?

In a data set with 20 variables, if 8% of the values, randomly spread across observations, are missing (blank) , what is the probable percent of complete and usable observations?

Using the simple mean imputation strategy, what value would be placed in the missing observation in x₁?

Using the simple mean imputation strategy, what value would be placed in the missing observation in x₁?

Using the omission strategy, what value would be placed in the missing observation in x₁?

Using the omission strategy, what value would be placed in the missing observation in x₁?

When performing an analysis, one technique is called RFM. Which of the following is not reflective of RFM?

In Analytic Solver, Aimee is trying to create a new column called RFM. This column is merging multiple values into one cell. The function to accomplish this is called?

The function that provides a natural logarithm in Excel is?

In R, Mary wants to understand the number of days between rain events in Chicago, IL. What function is used to find the number of rain events between today and January 1, 2019?

Quiz 2: Data Management and Wrangling

Which of the following is NOT a process of the data management system?

Which term represents data items, events, or things stored in a database file?

Mary in the accounting department has been assigned a specific vehicle as her company car to perform audits. This represents which type of relationship?

Select, From, and Where keywords are statements used in __________.

The primary purpose of a(n) _____________ is to support decision-making and provide a composite view of the organization.

A non-relational database structure that can support the storage of a wide ranges of data, including structured, semi-structured, and unstructured is called ___________.

Molly wants to view observations with missing values in Inventory. However, her data set is quite large. What functions should she use to complete her task in R?

In the presence of outliers in a data set, extremely small or large values, it is preferred to use the __________ instead of the ________ to impute missing variables.

In a data set with 18 variables, if 11% of the values, randomly spread across observations, are missing (blank) , what is the probable percent of complete and usable observations?

In a data set with 20 variables, if 8% of the values, randomly spread across observations, are missing (blank) , what is the probable percent of complete and usable observations?

Using the simple mean imputation strategy, what value would be placed in the missing observation in x1?

Using the simple mean imputation strategy, what value would be placed in the missing observation in x1?

Using the omission strategy, what value would be placed in the missing observation in x1?

Using the omission strategy, what value would be placed in the missing observation in x1?

When performing an analysis, one technique is called RFM. Which of the following is not reflective of RFM?

In Analytic Solver, Aimee is trying to create a new column called RFM. This column is merging multiple values into one cell. The function to accomplish this is called?

The function that provides a natural logarithm in Excel is?

In R, Mary wants to understand the number of days between rain events in Chicago, IL. What function is used to find the number of rain events between today and January 1, 2019?

In the presence of outliers in a data set, extremely small or large values, it is preferred to use the __ instead of the to impute missing variables.

Using the simple mean imputation strategy, what value would be placed in the missing observation in x₁?

Using the simple mean imputation strategy, what value would be placed in the missing observation in x₁?

Using the omission strategy, what value would be placed in the missing observation in x₁?

Using the omission strategy, what value would be placed in the missing observation in x₁?