2025年02月 CompTIA DA0-001認定リアル2025年最新の模擬試験合格させます
DA0-001試験問題と有効なDA0-001問題集でPDF
質問 # 51
What type of visualization allows the use of a bar chart for continuous variables?
- A. Histogram
- B. Waterfall chart
- C. Tree map
- D. Line chart
正解：A
質問 # 52
Which of the following would be considered non-personally identifiable information?
- A. Telephone number
- B. Government ID number
- C. Cell phone device name
- D. Customer's name
正解：C
解説：
Non-personally identifiable information (non-PII) is any data that cannot be used to identify, contact, or locate a specific individual, either alone or combined with other sources. Non-PII can include aggregated statistics, anonymous data, device identifiers, IP addresses, cookies, and other types of information that do not reveal the identity or location of a person. Cell phone device name is an example of non-PII, as it does not reveal any personal information about the owner or user of the device. Therefore, the correct answer is A. Reference: What is Non-Personally Identifiable Information (Non-PII)? | Definition and Examples, What is Personally Identifiable Information (PII)? | Definition and Examples
質問 # 53
Exhibit.
Which of the following logical statements results in Table B?
- A.
- B.
- C.
- D.
正解：D
解説：
Explanation
The logical statement that results in Table B is Option D. Option D is a logical statement that uses the AND operator to combine two conditions: Name = "Tom" and Region = "BC". The AND operator returns true only if both conditions are true, otherwise it returns false. Therefore, Option D will select only the rows from Table A that satisfy both conditions, which are rows 4, 5, 6, and 7. These rows form Table B, as shown below:
Name | Gender flag | Level | College | Code | Region Tom | Male | Elementary | A | BC | BC Kim | Female | Elementary | A | BC | BC Pat | Female | Elementary | A | BC | BC Ben | Male | Elementary | A | BC | BC The other options are not correct, as they use different logical operators or conditions that do not result in Table B. Option A uses the OR operator, which returns true if either condition is true, or both. Option A will select all the rows from Table A except row 3, which does not match either condition. Option B uses the NOT operator, which returns the opposite of the condition. Option B will select all the rows from Table A except rows 4, 5, 6, and 7, which match the condition. Option C uses a different condition, Region = "ON", which does not match any row in Table A. Option C will select no rows from Table A. Reference: [SQL Logical Operators - W3Schools]
質問 # 54
Which of the following is the correct data type for text?
- A. Float
- B. Integer
- C. Boolean
- D. String
正解：D
解説：
A string is a data type that represents a sequence of characters, such as text, symbols, numbers, or punctuation marks. Strings are enclosed in quotation marks, such as "Hello", "123", or "!@#". Strings can be manipulated, concatenated, sliced, indexed, formatted, and searched using various methods and functions. A string is different from other data types, such as boolean, integer, or float, which represent logical values (true or false), whole numbers, or decimal numbers respectively. Therefore, the correct answer is B. References:
What is a String? | Definition and Examples, Python String Methods
質問 # 55
Which of the following describes the method of sampling in which elements of data are selected randomly from each of the small subgroups within a population?
- A. Stratified
- B. Cluster
- C. Systematic
- D. Simple random
正解：A
解説：
This is because stratified is a type of sampling in which elements of data are selected randomly from each of the small subgroups within a population, such as age groups, gender groups, or income groups. Stratified sampling can be used to ensure that the sample is representative and proportional of the population, as well as reduce the sampling error or bias. For example, stratified sampling can be used to select a sample of voters from different political parties based on their proportion in the population. The other types of sampling are not the types of sampling in which elements of data are selected randomly from each of the small subgroups within a population. Here is why:
* Simple random is a type of sampling in which elements of data are selected randomly from the entire population, without dividing it into any subgroups. Simple random sampling can be used to ensure that every element in the population has an equal chance of being selected, as well as avoid any systematic error or bias. For example, simple random sampling can be used to select a sample of students from a school by using a lottery or a computer-generated number.
* Cluster is a type of sampling in which elements of data are selected randomly from a few large subgroups within a population, such as regions, districts, or schools. Cluster sampling can be used to reduce the cost and complexity of sampling, as well as increase the feasibility and convenience of sampling. For example, cluster sampling can be used to select a sample of households from a few neighborhoods by using a map or a list.
* Systematic is a type of sampling in which elements of data are selected at regular intervals from an ordered list or sequence within a population, such as every nth element or every kth element.
Systematic sampling can be used to simplify and speed up the sampling process, as well as ensure that the sample covers the entire range or scope of the population. For example, systematic sampling can be used to select a sample of books from a library by using an alphabetical order or a numerical order.
質問 # 56
Amanda needs to create a dashboard that will draw information from many other data sources and present it to business leaders.
Which one of the following tools is least likely to meet her needs?
- A. SPSS Modeler.
- B. Tableau.
- C. Power BI.
- D. QuickSight.
正解：A
解説：
Explanation
SPSS Modeler.
QuickSight, Tableau, and Power BI are all powerful analytics and reporting tools that can pull data from a variety of sources. SPSS Modeler is a powerful predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and your enterprise.
質問 # 57
A user receives a large custom report to track company sales across various date ranges. The user then completes a series of manual calculations for each date range. Which of the following should an analyst suggest so the user has a dynamic, seamless experience?
- A. Add macros to the report to speed up the filtering and calculations process.
- B. Build calculations into the report so they are done automatically.
- C. Create multiple reports, one for each needed date range.
- D. Create a dashboard with a date range picker and calculations built in.
正解：B
質問 # 58
The director of operations at a power company needs data to help identify where company resources should be allocated in order to monitor activity for outages and restoration of power in the entire state. Specifically, the director wants to see the following:
* County outages
* Status
* Overall trend of outages
INSTRUCTIONS:
Please, select each visualization to fit the appropriate space on the dashboard and choose an appropriate color scheme. Once you have selected all visualizations, please, select the appropriate titles and labels, if applicable.
Titles and labels may be used more than once.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
正解：
解説：
Power outages
Explanation:
This is a simulation question that requires you to create a dashboard with visualizations that meet the director' s needs. Here are the steps to complete the task:
* Drag and drop the visualization that shows the county outages on the top left space of the dashboard.
This visualization is a map of the state with different colors indicating the number of outages in each county. You can choose any color scheme that suits your preference, but make sure that the colors are consistent and clear. For example, you can use a gradient of red to show the counties with more outages and green to show the counties with less outages.
* Drag and drop the visualization that shows the status of the outages on the top right space of the dashboard. This visualization is a pie chart that shows the percentage of outages that are active, restored, or pending. You can choose any color scheme that suits your preference, but make sure that the colors are distinct and easy to identify. For example, you can use red for active, green for restored, and yellow for pending.
* Drag and drop the visualization that shows the overall trend of outages on the bottom space of the dashboard. This visualization is a line graph that shows the number of outages over time. You can choose any color scheme that suits your preference, but make sure that the color is visible and contrasted with the background. For example, you can use blue for the line and white for the background.
* Select appropriate titles and labels for each visualization. Titles and labels may be used more than once.
For example, you can use "County Outages" as the title for the map, "Status" as the title for the pie chart, and "Trend" as the title for the line graph. You can also use "County", "Number of Outages",
"Active", "Restored", "Pending", "Time", and "Number of Outages" as labels for the axes and legends of the visualizations.
質問 # 59
The sales grocery store had an average of $8000 per day. The store introduced several advertising campaigns in order to increase sales. To determine whether the advertising campaigns have been effective in increasing sales, a sample of 64 days of sales was selected, and the sample mean was $8000 per day.
The correct null and alternative hypotheses to test whether there has been a significant increase are
- A. Null Sample mean is $8000; Alternative Sample mean is greater than or equal to $8000.
- B. Null Sample mean is $8000; Alternative Sample mean is greater than $8000.
- C. Null Population mean is $8000; Alternative; Population mean is greater than $8000.
- D. Null Population mean is $8000; Alternative; Population mean is greater than or equal to $8000.
正解：C
解説：
Since you are trying to determine whether sales increased above the current average of $8000, the population mean for the null hypothesis is $8000; whereas the mean for the alternative hypothesis is greater than $8000. Hypotheses are always stated in terms of population you are working with, ruling out options A and B.
The test is whether sales are higher than the average of $8000 per day, which rules out option C.
質問 # 60
Which of the following is an example of a discrete data type?
- A. 2.5mi (4km)
- B. 10.7lbs (4.9kg)
- C. 8in (20cm)
- D. 5 kids
正解：D
解説：
A discrete data type is a data type that can only take on a finite number of values, such as integers or categories. An example of a discrete data type is the number of kids, as it can only be a whole number. The other options are examples of continuous data types, as they can take on any value within a range. The length in inches or centimeters, the distance in miles or kilometers, and the weight in pounds or kilograms are all continuous data types. Reference: CompTIA Data+ (DA0-001) Practice Certification Exams | Udemy
質問 # 61
What European law requires that organizations handling personal information designate a Data Protection Officer (DPO)?
- A. HIPAA (Health Insurance Portability and Accountability Act)
- B. FERPA (Family Educational Rights and Privacy Act)
- C. GLBA (Gramm-Leach-Bliley Act)
- D. GDPR (General Data Protection Regulation)
正解：D
解説：
The General Data Protection Regulation 2016/679 is a regulation in EU law on data protection and privacy in the European Union and the European Economic Area.
質問 # 62
A data analyst has been asked to organize the table below in the following ways:
By sales from high to low -
By state in alphabetic order -
Which of the following functions will allow the data analyst to organize the table in this manner?
- A. Conditional formatting
- B. Grouping
- C. Sorting
- D. Filtering
正解：C
解説：
Sorting is the function that will allow the data analyst to organize the table in the desired manner. Sorting means arranging the data in a specific order, such as ascending or descending, based on one or more criteria.
Sorting can be applied to any column in the table, such as sales or state. References: CompTIA Data+ Certification Exam Objectives, page 11
質問 # 63
'Which of the following is the BEST reason to use database views instead of tables?
- A. Views reduce the need for repetitive, complex data joins.
- B. Views allow for the storage of temporary data. whereas tables do not.
- C. Views can be used to restrict sensitive information.
- D. Views allow for the joining of multiple data sources, whereas tables do not.
正解：A
解説：
Views are virtual tables that are created by querying one or more base tables or other views. Views do not store any data, but only show the result of a query. One of the main advantages of using views is that they can reduce the need for repetitive, complex data joins. For example, if a query involves joining multiple tables with many conditions, creating a view can simplify the query and make it easier to reuse. Therefore, the correct answer is A. References: [What is a Database View? | Definition & Examples - Vertabelo], [Database Views - GeeksforGeeks]
質問 # 64
A data analyst was asked to create a chart that shows the relationship between study hours and exam scores for each student using the data sets in the table below:
Which of the following charts would BEST represent the relationship between the variables?
- A. A bar chart
- B. A scatter plot
- C. A heat map
- D. A histogram
正解：B
解説：
Explanation
This is because a scatter plot is a type of chart that shows the relationship between two variables for each observation or unit in a data set, such as study hours and exam scores for each student in this case. A scatter plot can be used to display and analyze the correlation, trend, or pattern among the variables, as well as identify any outliers or clusters in the data. For example, a scatter plot can show if there is a positive, negative, or no correlation between study hours and exam scores, as well as show if there are any students who have unusually high or low exam scores compared to their study hours. The other charts are not the best charts to represent the relationship between the variables. Here is why:
A histogram is a type of chart that shows the frequency or the count of values in a single variable for different intervals or bins, such as exam scores for different ranges in this case. A histogram can be used to display and analyze the distribution, shape, or spread of the variable, as well as identify any gaps, peaks, or skewness in the data. For example, a histogram can show if most students have high, low, or average exam scores, as well as show if there are any intervals that have no students at all.
A heat map is a type of chart that shows the intensity or the magnitude of values in two variables for different categories or groups, such as exam scores and study hours for different student names in this case. A heat map can be used to display and analyze the variation, contrast, or comparison among the categories or groups, as well as identify any hot spots, cold spots, or gradients in the data. For example, a heat map can show which students have higher or lower exam scores and study hours than others, as well as show if there is a color pattern that indicates a relationship between exam scores and study hours.
A bar chart is a type of chart that shows the value or the amount of a single variable for different categories or groups, such as exam scores for different student names in this case. A bar chart can be used to display and analyze the comparison, ranking, or proportion among the categories or groups, as well as identify any differences, similarities, or outliers in the data. For example, a bar chart can show which students have higher or lower exam scores than others, as well as show if there are any students who have exceptionally high or low exam scores.
質問 # 65
An analyst is working with the income data of suburban families in the United States. The data set has a lot of outliers, and the analyst needs to provide a measure that represents the typical income. Which of the following would BEST fulfill the analyst's goal?
- A. Median
- B. Mode
- C. Standard deviation
- D. Mean
正解：A
解説：
his is because median is a type of statistical measure that represents the typical value or central tendency of a data set, which means that it divides the data set into two equal halves, such that half of the values are above it and half are below it. Median can be used to provide a measure that represents the typical income of suburban families in the United States, especially when the data set has a lot of outliers, which means that it has values that are unusually high or low compared to the rest of the data set. Median can provide a measure that represents the typical income of suburban families in the United States, because it is not affected or skewed by the outliers, as it only depends on the middle value or the middle two values of the data set, regardless of how extreme or distant the outliers are. For example, median can provide a measure that represents the typical income of suburban families in the United States, by finding the income value that splits the data set into two equal groups of families, such that 50% of the families have higher incomes and 50% have lower incomes.
The other statistical measures are not the best measures to represent the typical income of suburban families in the United States. Here is why:
* Mean is a type of statistical measure that represents the average value or central tendency of a data set, which means that it is the sum of all the values divided by the number of values. Mean is not a good measure to represent the typical income of suburban families in the United States, especially when the data set has a lot of outliers, because it is affected or skewed by the outliers, as it takes into account all the values in the data set, regardless of how extreme or distant they are. For example, mean can provide a measure that does not represent the typical income of suburban families in the United States, by finding the income value that is influenced by a few very high or very low incomes, which could make it higher or lower than most of the incomes in the data set.
* Mode is a type of statistical measure that represents the most frequent value or mode of a data set, which means that it is the value that occurs most often in the data set. Mode is not a good measure to represent the typical income of suburban families in the United States, especially when the data set has a lot of outliers, because it is not representative or indicative of the central tendency or distribution of the data set, as it only depends on the count or occurrence of a single value or a few values in the data set, regardless of how common or rare they are. For example, mode can provide a measure that does not represent the typical income of suburban families in the United States, by finding the income value that is repeated more often than others, which could be an outlier or an anomaly in the data set.
* Standard deviation is a type of statistical measure that represents the amount of dispersion or variation of a data set, which means that it quantifies how much the values in a data set vary or deviate from the mean or average of the data set. Standard deviation is not a measure that represents the typical income of suburban families in the United States, but rather a measure that describes the spread or distribution of their incomes, as well as identifies any outliers or extreme values in their incomes. For example, standard deviation can provide a measure that describes how diverse or homogeneous their incomes are, as well as how far their incomes are from their average income.
質問 # 66
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 for sales numbers, pipeline, and team and individual performance for the management team.
- B. Create a dashboard displaying a data refresh date so users know the current sales numbers and configure permissions to control access.
- 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.
正解：D
解説：
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.
質問 # 67
A data analyst is designing a dashboard that will provide a story of sales and determine which site is providing the highest sales volume per customer. The analyst must choose an appropriate chart to include in the dashboard. The following data is available:
Which of the following types of charts should be considered?
- A. Include a pie chart using the site and sales to average sales per customer.
- B. Include a scatter chart using sales volume and average sales per customer.
- C. Include a line chart using the site and average sales per customer.
- D. Include a column chart using the site and sales to average sales per customer.
正解：B
解説：
A scatter chart using sales volume and average sales per customer is the best type of chart to include in the dashboard. A scatter chart is a type of chart that displays the relationship between two numerical variables using dots or markers. A scatter chart can show how one variable affects another, how strong the correlation is between them, and how the data points are distributed. In this case, a scatter chart can show the story of sales and determine which site is providing the highest sales volume per customer by plotting the sales volume on the x-axis and the average sales per customer on the y-axis. Each dot on the chart will represent a site, and the analyst can easily compare the sites based on their position on the chart. A site with a high sales volume and a high average sales per customer will be in the upper right quadrant, indicating a high performance. A site with a low sales volume and a low average sales per customer will be in the lower left quadrant, indicating a low performance. A site with a high sales volume and a low average sales per customer will be in the lower right quadrant, indicating a high volume but low value. A site with a low sales volume and a high average sales per customer will be in the upper left quadrant, indicating a low volume but high value. A scatter chart can also show if there is a positive or negative correlation between the two variables, or if there is no correlation at all.
A positive correlation means that as one variable increases, so does the other. A negative correlation means that as one variable increases, the other decreases. No correlation means that there is no relationship between the two variables.
The other types of charts are not as suitable for this purpose. A line chart is a type of chart that displays the change of one or more variables over time using lines. A line chart can show trends, patterns, and fluctuations in the data. However, in this case, there is no time variable involved, so a line chart would not be appropriate.
A pie chart is a type of chart that displays the proportion of each category in a whole using slices of a circle.
A pie chart can show how each category contributes to the total and compare the relative sizes of each category. However, in this case, there are two numerical variables involved, so a pie chart would not be able to show their relationship. A column chart is a type of chart that displays the comparison of one or more variables across categories using vertical bars. A column chart can show how each category differs from each other and rank them by size. However, in this case, a column chart would not be able to show the relationship between sales volume and average sales per customer, as it would only show one variable for each site.
質問 # 68
A marketing analytics team received customer transaction data from two different sources. The data is complete and accurate; however, the field names appear to be inconsistent. Given the following tables:
Which of the following is considered best practice if the team wants to consolidate the files and conduct further analysis?
- A. Overwrite the field names in one of the tables.
- B. Recode the data values.
- C. Standardize the field names.
- D. Edit the field names in the data dictionary.
正解：C
質問 # 69
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