CompTIA DA0-001 Online Practice Questions and Exam Preparation

CompTIA DA0-001 Online Questions & Answers

• Question 181:

  A survey asks participants to rate a company on a scale of one to ten. Which of the following best describes the rating variable?

  A. Continuous
  B. Ordinal
  C. Categorical
  D. Nominal
  B. Ordinal

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  Explanation

  The rating variable in a survey where participants rate a company on a scale of one to ten is best described as ordinal. This is because the ratings are ranked in order, with each number representing a position on a scale of satisfaction or

  quality. The numbers are not just labels (which would be nominal), nor do they represent a continuous spectrum (which would be continuous). They also do not fit the definition of categorical, as that implies non- ordered groups or categories.

  In an ordinal scale, the order of the values is significant and meaningful.

  References:

  Qualtrics explains that ordinal scales have answer sets that occur in a logical and systematic order, providing qualitative data. Zonka Feedback describes a 1 to 10 rating scale survey, indicating that the numbers represent a ranking from most

  negative to most positive experience, which aligns with the characteristics of an ordinal scale.

• Question 182:

  Which of the following is the best reason for removing data outliers?

  A. Data varies significantly from others.
  B. Data is redundant in the table.
  C. Data is duplicated in the whole range.
  D. Data is missing from the table.
  A. Data varies significantly from others.

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  Explanation

• Question 183:

  While reviewing survey data, a research analyst notices data is missing from all the responses to a single question.

  Which of the following methods would BEST address this issue?

  A. Replace missing data.
  B. Remove duplicate data.
  C. Replace redundant data.
  D. Remove invalid data.
  A. Replace missing data.

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  Explanation

  This is because missing data is a type of data quality issue that occurs when data is absent or incomplete in a data set, which can affect the accuracy and reliability of the analysis or process. Missing data can be caused by various factors, such as human error, system error, or non-response. Missing data can be addressed by using various methods, such as replacing missing data, which means filling in or imputing the missing values with some reasonable estimates, such as mean, median, mode, or regression. The other methods are not used to address missing data. Here is why:

  Remove duplicate data is a type of method that eliminates or reduces duplicate data, which is a type of data quality issue that occurs when data is repeated or copied in a data set. Removing duplicate data does not address missing data, but rather affects the quantity and validity of the data. Replace redundant data is a type of method that eliminates or reduces redundant data, which is a type of data quality issue that occurs when data is unnecessary or irrelevant for the analysis or purpose. Replacing redundant data does not address missing data, but rather affects the efficiency and performance of the analysis or process. Remove invalid data is a type of method that eliminates or reduces invalid data, which is a type of data quality issue that occurs when data is incorrect or inaccurate in a data set. Removing invalid data does not address missing data, but rather affects the validity and reliability of the analysis or process.

• Question 184:

  Which of the following is a common data analytics tool that is also used as an interpreted, high-level, general-purpose programming language?

  A. SAS
  B. Microsoft Power B1
  C. IBM SPSS
  D. Python
  D. Python

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  Explanation

  The option that is a common data analytics tool that is also used as an interpreted, high-level, general-purpose programming language is Python. Python is a popular and versatile programming language that can be used for various

  purposes, such as web development, software development, automation, machine learning, and data analysis. Python has many features and libraries that make it suitable for data analytics, such as its simple syntax, dynamic typing, multiple

  paradigms, built-in data structures, NumPy, pandas, matplotlib, scikit-learn, etc. The other options are not programming languages, but software applications or platforms that are used for data analytics or related tasks. SAS is a software suite

  that provides advanced analytics, business intelligence, data management, and predictive analytics capabilities. Microsoft Power BI is a business analytics service that provides interactive visualizations and business intelligence capabilities.

  IBM SPSS is a software package that offers statistical analysis, data mining, text analytics, and predictive analytics capabilities.

  Python For Data Analysis - DataCamp

• Question 185:

  A data analyst needs to calculate the mean for Q1 sales using the data set below:

  

  Which of the following is the mean?

  A. $2,466.18
  B. $2,667.60
  C. $3,082.72
  D. $12,330.88
  C. $3,082.72

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  Explanation

  The mean is the average of all the values in a data set. To calculate the mean, we add up all the values and divide by the number of values. In this case, the mean for Q1 sales is ($2,000 + $3,000 + $4,000 + $2,500 + $3,500) / 5 = $3,082.72

  References:

  CompTIA Data+ Certification Exam Objectives, page 9

• Question 186:

  A data analyst is developing a data dictionary that aligns with a company's data management processes and policies.

  Which of the following best describes what should be included in the data dictionary?

  A. Information containing the links to business data
  B. Information explaining the business methodologies
  C. Information containing definitions of the business data
  D. Information describing the data analysis phases
  C. Information containing definitions of the business data

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  Explanation

• Question 187:

  Which of the following types of analysis would be best for an analyst to use to examine the relationships between authors who cited other authors in a library of research papers?

  A. Linguistic analysis
  B. Trend analysis
  C. Link analysis
  D. Performance analysis
  C. Link analysis

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  Explanation

• Question 188:

  A data analyst is creating a report that will provide information about various regions, products, and time periods.

  Which of the following formats would be the most efficient way to deliver this report?

  A. A workbook with multiple tabs for each region
  B. A daily email with snapshots of regional summaries
  C. A static report with a different page for every filtered view
  D. A dashboard with filters at the top that the user can toggle
  D. A dashboard with filters at the top that the user can toggle

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  Explanation

  The best format to deliver this report is

  D. A dashboard with filters at the top that the user can toggle. A dashboard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance. A dashboard with filters at the top that the user can toggle would allow the user to easily and quickly access the information they need about various regions, products, and time periods, without having to navigate through multiple tabs, pages, or emails. A dashboard with filters would also enable the user to compare and contrast different views of the data and see how they change over time. A dashboard with filters would also be more interactive and engaging than a static or email report. A workbook with multiple tabs for each region would not be an efficient way to deliver this report, because it would require the user to switch between different tabs to see the information they need. This would make it harder to compare and contrast different regions, products, and time periods, and also increase the risk of errors or confusion. A workbook with multiple tabs would also be less visually appealing and more cluttered than a dashboard. A daily email with snapshots of regional summaries would not be an efficient way to deliver this report, because it would limit the user's ability to explore the data in depth and customize their view. A daily email would also be dependent on the frequency and timing of the email delivery, which might not match the user's needs or preferences. A daily email would also be more likely to be ignored or deleted than a dashboard that is always accessible. A static report with a different page for every filtered view would not be an efficient way to deliver this report, because it would create a very long and cumbersome report that would be difficult to read and understand. A static report would also not allow the user to change or update the filters as they wish, or see how the data changes over time. A static report would also be less interactive and engaging than a dashboard.

• Question 189:

  The duration of a phone call in milliseconds is an example of:

  A. ordinal data.
  B. nominal data.
  C. boolean data.
  D. continuous data.
  D. continuous data.

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  Explanation

  The correct answer is

  D. Continuous data. Continuous data is a type of quantitative data that can take any value within a range and can be measured with infinite precision. Continuous data can be expressed as fractions, decimals, or percentages. Examples of continuous data are height, weight, temperature, time, speed, etc. The duration of a phone call in milliseconds is an example of continuous data, because it can take any value within a range (from zero to infinity) and can be measured with infinite precision (up to milliseconds or even smaller units). The duration of a phone call in milliseconds can also be expressed as fractions, decimals, or percentages of a larger unit (such as seconds, minutes, or hours). Ordinal data is not correct, because ordinal data is a type of qualitative or categorical data that can be ordered or ranked according to some criterion. Ordinal data can have a logical order, but the intervals between the values are not equal or meaningful. Examples of ordinal data are grades, ratings, ranks, etc. Nominal data is not correct, because nominal data is a type of qualitative or categorical data that can be labeled or named without any order or ranking. Nominal data can have a finite number of categories or classes, but the categories have no intrinsic value or hierarchy. Examples of nominal data are gender, color, nationality, etc. Boolean data is not correct, because boolean data is a type of binary data that can have only two possible values: true or false. Boolean data can be used to represent logical statements, conditions, or outcomes. Examples of boolean data are yes/no, on/off, 1/0, etc.

• Question 190:

  An analyst wants to create a historical data set for the past five years with each year in its own data set.

  Which of the following methods is the best way to create this historical data set?

  A. Data transpose
  B. Data concatenation
  C. Data append
  D. Data normalization
  B. Data concatenation

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  Explanation