Data Collection and Preparation for Business Analytics and Data Science

Question 1

Revised: What is the primary objective of data collection in business analytics?

Accepted Answer

Revised: To acquire relevant information for analysis and decision-making

Answer

Revised: To improve business operations through data-driven insights

Answer

Revised: To test hypotheses and validate assumptions

Answer

Revised: To create visually appealing reports and presentations

Question 2

Revised: What is a technique used to address missing data in a dataset?

Accepted Answer

Revised: Imputation

Answer

Revised: Exclusion

Answer

Revised: Transformation

Answer

Revised: Aggregation

Question 3

When collecting data through surveys, which of the following can introduce bias?

Accepted Answer

Asking questions that lead respondents towards a particular answer

Answer

Using a random sample

Answer

Collecting data from a large sample size

Answer

Transforming the data into a different format

Question 4

Which data cleaning technique is specifically designed to eliminate duplicate rows within a dataset?

Accepted Answer

De-duplication

Answer

Imputation

Answer

Normalization

Question 5

What is a common technique for dealing with missing data in a dataset?

Accepted Answer

Imputation

Answer

Normalization

Answer

Aggregation

Answer

Clustering

Question 6

Which data cleaning technique is used to estimate and replace missing values in data?

Accepted Answer

Data imputation

Answer

Data scrubbing

Answer

Data transformation

Answer

Data validation

Question 7

Which method is most effective in protecting consumer privacy when businesses collect and use personal data?

Accepted Answer

Anonymising data before analysis

Answer

Storing data on password-protected computers

Answer

Obtaining written consent from consumers before data collection

Question 8

Which of the following methods is primarily used to collect qualitative data?

Accepted Answer

Interviews

Answer

Surveys (Quantitative)

Answer

Observation

Answer

Experiments

Question 9

What is the term for the process of identifying and removing duplicate or irrelevant observations from a dataset?

Accepted Answer

Data cleaning

Answer

Data integration

Answer

Data standardization

Answer

Data transformation

Question 10

What is the primary reason for handling missing values in a dataset?

Accepted Answer

To prevent potential errors and biases in subsequent data analysis

Answer

To reduce the complexity and size of the dataset

Answer

To enhance the overall appearance of the data

Answer

To ensure data consistency across different sources

Question 11

What is the purpose of data transformation in the data preparation process?

Accepted Answer

To convert data into a format suitable for analysis

Answer

To visualize data in a clear and concise manner

Answer

To create data models for visualization purposes

Answer

To clean and remove errors from the data

Question 12

Which of the following is a key advantage of utilizing external data sources?

Accepted Answer

Access to a wider range and variety of data

Answer

Elimination of potential biases inherent in the data

Answer

Guaranteed improvement in the accuracy and reliability of the data

Answer

Significant reduction in data collection costs

Question 13

What is the primary significance of maintaining data provenance?

Accepted Answer

To ensure the trustworthiness and validity of the data

Answer

To enhance the visual representation of the data

Answer

To minimize the storage space required for the data

Answer

To improve the accessibility and usability of the data

Question 14

What is the overarching objective of data cleaning?

Accepted Answer

To enhance the overall quality of the data

Answer

To simplify the process of data analysis

Answer

To reduce the volume and size of the data

Answer

To improve the visual appeal of the data

Question 15

Which of the following is an example of a data transformation technique?

Accepted Answer

Logarithmic transformation

Answer

Data extraction

Answer

Data aggregation

Question 16

**Which of the following is a primary benefit of using a structured questionnaire for data collection?**

Accepted Answer

Enhanced data quality through standardized responses and reduced ambiguity

Answer

Lower cost of data collection

Answer

Increased response rate

Answer

Reduced time to collect data

Question 17

**What is the primary purpose of data cleaning?**

Accepted Answer

To remove errors, inconsistencies, and duplicate data to improve data quality

Answer

To identify missing values and outliers

Answer

To transform data into a suitable format for analysis

Question 18

**What is the primary role of exploratory data analysis (EDA) in data preparation?**

Accepted Answer

To identify patterns, trends, and outliers in the data to gain insights and inform further analysis

Answer

To transform data into a suitable format for analysis

Answer

To clean and prepare data for modeling

Question 19

**What is the fundamental distinction between supervised and unsupervised learning?**

Accepted Answer

Supervised learning involves labeled data, while unsupervised learning does not

Answer

Supervised learning is used for classification, while unsupervised learning is used for regression

Answer

Unsupervised learning requires more data than supervised learning

Question 20

**Which of the following is an example of a structured data source?**

Accepted Answer

A database

Answer

A website

Answer

A social media platform

Answer

An email inbox

Question 21

**What is the overarching purpose of data validation?**

Accepted Answer

To ensure the accuracy, completeness, and consistency of data

Answer

To identify missing values and outliers

Answer

To prepare data for analysis

Question 22

**Which of the following is a best practice for data collection?**

Accepted Answer

Triangulating findings using multiple data sources enhances data reliability

Answer

Ignore ethical considerations when collecting data

Answer

Collect data from as many sources as possible without regard to relevance

Answer

Focus solely on collecting quantitative data

Question 23

**What is the difference between accuracy and precision in data measurement?**

Accepted Answer

Accuracy refers to how close the measurement is to the true value, while precision refers to how consistent the measurements are

Answer

Accuracy and precision are synonymous terms

Question 24

Which of the following is NOT a benefit of data preparation?

Accepted Answer

Increases data inaccuracy

Answer

Improves data quality

Answer

Facilitates data analysis

Answer

Enhances data accuracy

Question 25

What is the most common method for handling missing data?

Accepted Answer

Imputation

Answer

Transformation

Answer

Smoothing

Answer

Deletion

Question 26

What is the primary purpose of data cleaning?

Accepted Answer

To detect and correct errors and inconsistencies in the data

Answer

To transform data into a desired format

Answer

To prepare data for analysis

Answer

To identify patterns and trends in the data

Question 27

Which of the following is a key best practice for data collection?

Accepted Answer

Define clear objectives and identify the specific purpose of the data collection

Answer

Collect as much data as possible, regardless of relevance

Answer

Rely solely on secondary data sources

Question 28

What is the fundamental difference between primary and secondary data?

Accepted Answer

Primary data is collected firsthand by the researcher, while secondary data has already been gathered by others

Answer

Primary data is inherently more reliable than secondary data

Answer

Primary data is qualitative, while secondary data is quantitative

Question 29

Which of the following is a useful tool for identifying outliers in a dataset?

Accepted Answer

Box plot

Answer

Line graph

Answer

Scatter plot

Answer

Histogram

Question 30

What is the main purpose of data normalization?

Accepted Answer

To transform data to a specific range or distribution

Answer

To convert data into a binary format

Answer

To handle missing data values

Answer

To eliminate outliers from the data

Question 31

What is the ultimate goal of data preparation?

Accepted Answer

To convert raw data into a format suitable for analysis

Answer

To draw conclusions from the data

Answer

To identify patterns and trends in the data

Question 32

What is the process of removing errors and inconsistencies from data known as?

Accepted Answer

Data cleaning

Answer

Data transformation

Answer

Data analysis

Question 33

What is the process of converting data into a suitable format for analysis called?

Accepted Answer

Data transformation

Answer

Data visualization

Answer

Data normalization

Answer

Data cleaning

Question 34

Which technique is used to identify outliers in data?

Accepted Answer

Z-score analysis

Answer

Correlation analysis

Answer

Regression analysis

Answer

Cluster analysis

Question 35

What is the purpose of data normalization?

Accepted Answer

To standardize data within a specific range

Answer

To detect outliers

Answer

To convert data to a different format

Answer

To remove missing values

Question 36

Which of the following is a type of sampling technique?

Accepted Answer

Random sampling

Answer

Outlier detection

Answer

Data transformation

Answer

Data cleaning

Question 37

What is the process of selecting a representative subset of data from a larger dataset called?

Accepted Answer

Sampling

Answer

Data visualization

Answer

Data transformation

Answer

Data cleaning

Question 38

What is the main objective of data validation?

Accepted Answer

To ensure data accuracy and consistency

Answer

To identify missing values

Answer

To convert data to a different format

Answer

To detect outliers

Question 39

Which of the following data collection methods specifically involves obtaining quantifiable numerical data?

Accepted Answer

Survey

Answer

Interview

Answer

Observation

Answer

Focus group

Question 40

What is the process of identifying and correcting errors or inconsistencies in data known as?

Accepted Answer

Data cleaning

Answer

Data transformation

Answer

Data summarization

Answer

Data normalization

Question 41

Which approach to dealing with missing values involves removing all instances/rows containing missing data?

Accepted Answer

Delete all rows with missing values

Answer

Use a machine learning algorithm to predict missing values

Answer

Create a new category for missing values

Answer

Impute missing values using mean or median

Question 42

What is the primary objective of performing data transformation?

Accepted Answer

To prepare data for analysis by converting it into a suitable format

Answer

To remove outliers from the data

Answer

To reduce the dimensionality of the data

Question 43

Which technique for data normalization involves scaling data to the range 0 to 1?

Accepted Answer

Min-max normalization

Answer

Outlier removal

Answer

Data imputation

Answer

Binning

Question 44

Which step should be the initial phase in the data preparation process?

Accepted Answer

Data collection

Answer

Data cleaning

Answer

Data analysis

Answer

Data transformation

Question 45

Which of the following is a key advantage of storing data in a structured format?

Accepted Answer

Facilitates efficient analysis and processing

Answer

Provides better security than unstructured data

Answer

Requires minimal storage space

Answer

Guarantees higher accuracy compared to unstructured data

Question 46

What is the primary purpose of data validation?

Accepted Answer

To ensure that the data adheres to the requirements of the analysis

Answer

To convert data into a suitable format

Answer

To eliminate outliers from the data

Question 47

What is a primary benefit of performing data preparation?

Accepted Answer

Enhanced accuracy, consistency, and efficiency in data analysis

Answer

Improved visual appeal of the data

Answer

Reduced costs associated with data analysis

Question 48

What is the process of verifying and correcting errors in raw data called?

Accepted Answer

Data cleaning

Answer

Data analysis

Answer

Data visualization

Answer

Data preparation

Question 49

Which type of data transformation is used to convert categorical data into numerical values?

Accepted Answer

One-hot encoding

Answer

Discretization

Answer

Normalization

Answer

Binning

Question 50

Which of the following is a type of data source?

Accepted Answer

Structured

Answer

Imputed

Answer

Transformed

Answer

Aggregated

Question 51

What is the primary goal of data preparation?

Accepted Answer

To ensure the data is suitable for analysis

Answer

To interpret the data

Answer

To reduce the size of the data

Answer

To visualize the data