CompTIA DA0-001 Online Practice Questions and Exam Preparation

CompTIA DA0-001 Online Questions & Answers

• Question 261:

  The current date is July 14, 2020. A data analyst has been asked to create a report that shows the company's year-over-year Q2 2020 sales.

  Which of the following reports should the analyst compare?

  A. Q2 2020 and Q4 2019
  B. YTD 2020 and YTD 2019
  C. Q2 2020 and Q2 2019
  D. Q2 2020 and Q2 2021
  C. Q2 2020 and Q2 2019

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  Explanation

  Year-over-year (YoY) comparison is a method of evaluating two or more measured events to compare the results at one period with those from a comparable period on an annual basis. For a year-over-year comparison of Q2 2020 sales, the

  analyst should compare the sales figures from Q2 2020 with those from Q2 2019. This comparison will show the growth, stagnation, or decline in sales over the year and is a common practice in financial analysis to assess performance.

  References:

  SlideTeam's article on sales comparison templates.

  Salesforce help article on calculating YoY or Quarter-over-Quarter (QoQ) in reports.

  Smartsheet's content on annual sales report templates.

  TechRepublic article on creating a YoY comparison chart using a PivotChart in Excel.

• Question 262:

  An analyst modified a data set that had a number of issues. Given the original and modified versions:

  

  Which of the following data manipulation techniques did the analyst use?

  A. Imputation
  B. Recoding
  C. Parsing
  D. Deriving
  B. Recoding

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  Explanation

  The correct answer is

  B. Recoding.

  Recoding is a data manipulation technique that involves changing the values or categories of a variable to make it more suitable for analysis. Recoding can be used to simplify or group the data, to correct errors or inconsistencies, or to create

  new variables from existing ones.

  In the example, the analyst used recoding to change the values of Var001, Var002, Var003, and Var004 from numerical to textual form. The analyst also used recoding to assign meaningful labels to the values, such as "Absent" for 0,

  "Present" for 1, "Low" for 2, "Medium" for 3, and "High" for 4. This makes the data more understandable and easier to analyze.

• Question 263:

  A sales team wants visibility of current sales numbers, pipeline, and team performance. The team would also like to see calculations of individuals' earned commissions and projected commissions based on sales, but they want that information to be kept confidential.

  Which of the following would be the BEST way to provide this visibility?

  A. Create a dashboard displaying a data refresh date so users know the current sales numbers and configure permissions to control access.
  B. Create a dashboard for sales numbers, pipeline, and team and individual performance for the management team.
  C. Create a dashboard with filters for the overall team, individuals, and management. Users can filter to see the data they want.
  D. Create a dashboard with views for team, individuals, and management. Configure permissions to control access.
  D. Create a dashboard with views for team, individuals, and management. Configure permissions to control access.

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  Explanation

  Create a dashboard with views for team, individuals, and management. Configure permissions to control access. This is because a dashboard is a type of visualization that displays multiple charts or graphs on a single page, usually to provide

  an overview or summary of some data or information. A dashboard can be used to provide visibility of current sales numbers, pipeline, and team performance by showing different metrics and indicators related to these aspects. By creating a

  dashboard with views for team, individuals, and management, the analyst can customize the content and layout of the dashboard for different audiences and purposes. By configuring permissions to control access, the analyst can ensure that

  the confidential information, such as individuals' earned commissions and projected commissions based on sales, is only visible to the authorized users. The other ways are not the best way to provide this visibility. Here is why:

  Creating a dashboard displaying a data refresh date so users know the current sales numbers and configuring permissions to control access would not be sufficient to provide visibility of pipeline and team performance, as well as individuals'

  earned commissions and projected commissions based on sales. The dashboard would only show the current sales numbers and the date when the data was updated, which would not give a comprehensive or detailed view of the sales

  situation.

  Creating a dashboard for sales numbers, pipeline, and team and individual performance for the management team would not be appropriate to provide visibility for the sales team, as they would not have access to the dashboard or the

  information they need. The dashboard would only be available for the management team, which would limit the transparency and collaboration among the sales team members. Creating a dashboard with filters for the overall team,

  individuals, and management would not be secure to provide visibility of confidential information, such as individuals' earned commissions and projected commissions based on sales. The dashboard would allow users to filter and see the

  data they want, which could expose sensitive or personal information to unauthorized users.

• Question 264:

  A sales manager requested a report that contains the first name, last name, and phone number of all the company's customers and employees. The data engineer needs to return all the records from several tables, even duplicates. Which of the following is the best way to join the two tables?

  A. FULL OUTER JOIN
  B. INNER JOIN
  C. LEFT OUTER JOIN
  D. CROSS JOIN
  D. CROSS JOIN

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  Explanation

• Question 265:

  Standardized tests are given to students in the middle of each month, and the results are ready by the end of the month. The superintendent needs a quick view of test performance.

  Which of the following would be the best recommendation to meet the superintendent's requirements?

  A. A dashboard with a continuous data stream and saved searches
  B. A report of test scores by classroom, emailed to the superintendent at the end of the month
  C. A report of test scores with pie charts showing student performance
  D. A dashboard with a scheduled delivery, the ability to filter scores by school, and bar charts for comparison
  D. A dashboard with a scheduled delivery, the ability to filter scores by school, and bar charts for comparison

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  Explanation

  A dashboard with a scheduled delivery is an efficient way to provide a quick view of test performance. It allows for timely updates, which is crucial given that the superintendent needs the information promptly at the end of each month. The

  ability to filter scores by school enables the superintendent to easily segment and analyze the data as needed. Bar charts are effective for comparison and can visually communicate the performance across different schools or other

  categories, making it easier to identify trends and outliers at a glance.

  References:

  Best practices in data visualization recommend using dashboards for real-time data monitoring and quick access to key metrics.

  Guidelines for presenting performance data suggest that visual tools like bar charts are helpful in comparing and analyzing data effectively. Educational performance data analysis often involves comparing scores across different schools or

  classrooms, which is facilitated by a well-designed dashboard.

• Question 266:

  A data analyst has a set of data that shows the number of gallons of oil produced each day. The company would like to know the standard deviation for the data set. The variance for the data is 36 gallons.

  Which of the following is the standard deviation for gallons produced?

  A. 1.16
  B. 6
  C. 36
  D. 72
  B. 6

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  Explanation

  The standard deviation is a measure of the amount of variation or dispersion in a set of values. It is calculated as the square root of the variance. Given that the variance for the data set is 36 gallons, the standard deviation can be found by

  taking the square root of 36, which is 6. Therefore, the standard deviation for the number of gallons of oil produced each day is 6 gallons.

  References:

  The concept of standard deviation and its calculation is a fundamental aspect of statistics, which is well-documented in statistical textbooks and resources. The calculation performed to arrive at the answer is based on the mathematical

  operation of taking the square root of the variance value.

• Question 267:

  Joseph is interpreting a left skewed distribution of test scores. Joe scored at the mean, Alfonso scored at the median, and gaby scored and the end of the tail.

  Who had the highest score?

  A. Joseph
  B. Joe
  C. Alfonso
  D. Gaby
  C. Alfonso

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  Explanation

  Alfonso had the highest score. A left skewed distribution is a distribution where the tail is longer on the left side than on the right side, meaning that most of the values are clustered on the right side and there are some outliers on the left side. In a left skewed distribution, the mean is less than the median, which is less than the mode. Therefore, Joseph, who scored at the mean, had the lowest score, Gaby, who scored at the end of the tail, had the second lowest score, and

  Alfonso, who scored at the median, had the highest score.

• Question 268:

  Given the diagram below:

  

  Which of the following types of sampling is depicted in the image?

  A. Stratified
  B. Random
  C. Cluster
  D. Systematic
  D. Systematic

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  Explanation

  Systematic sampling is a type of sampling where the sample is selected by following a fixed interval. For example, every 10th person in a list is chosen for the sample. In the image, the sample is selected by choosing every 3rd person in the

  line, starting from person number. This is an example of systematic sampling.

  References:

  Types of Sampling Techniques in Data Analytics You Should Know, Sampling Methods | Types, Techniques and Examples - Scribbr

• Question 269:

  A data analyst has received a data set that contains actual and projected sales for the fourth quarter of 2019.

  Which of the following statistical methods should the analyst use to find the measure of dispersion?

  A. Mean
  B. Variance
  C. Correlation
  D. Confidence interval
  B. Variance

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  Explanation

  The measure of dispersion is used to describe the spread of data around a central value. In the context of a data set containing actual and projected sales, the measure of dispersion will help to understand the variability or consistency of sales figures. The variance is the most appropriate statistical method for finding the measure of dispersion because it calculates the average of the squared differences from the Mean, providing a clear picture of data spread. It is especially useful in comparing the spread between different data sets and understanding the distribution of data points. Mean is a measure of central tendency, not dispersion. Correlation measures the relationship between two variables, not the spread of a single variable. Confidence intervals are used to estimate the range within which a population parameter will fall, but they do not measure dispersion within the data set itself.

  References: Measures of Dispersion in Statistics Measures of Dispersion - Definition, Formulas, Examples Statistical dispersion - Wikipedia

• Question 270:

  Which of the following data manipulation techniques is an example of a logical function?

  A. WHERE
  B. AGGREGATE
  C. BOOLEAN
  D. IF
  D. IF

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  Explanation

  This is because an IF function is a type of logical function that returns a value based on a condition or a set of conditions. An IF function can be used to manipulate data by applying different actions or calculations depending on whether the

  condition is true or false. For example, an IF function in Excel that can achieve this is:

  =IF (condition, value_if_true, value_if_false)

  The other data manipulation techniques are not examples of logical functions. Here is why:

  WHERE is a type of clause that filters data based on a condition or a set of conditions. A WHERE clause can be used to manipulate data by selecting only the rows that satisfy the condition(s). For example, a WHERE clause in SQL that can

  achieve this is:

  

  AGGREGATE is a type of function that performs a calculation on a group of values, such as sum, average, count, etc. An AGGREGATE function can be used to manipulate data by summarizing or aggregating the values in a column or a table. For example, an AGGREGATE function in SQL that can achieve this is:

  

  BOOLEAN is a type of data type that represents two possible values: true or false. A BOOLEAN data type can be used to manipulate data by storing or returning logical values based on a condition or a set of conditions. For example, a BOOLEAN data type in Python that can achieve this is: