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CompTIA Data+ Certification Exam DA0-001 Prüfungsfragen mit Lösungen (Q290-Q295):

290. Frage
The process of performing initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization is called:

• A. a performance analysis.
• B. a t-test.
• C. a link analysis.
• D. an exploratory data analysis.

Antwort: D

Begründung:
This is because exploratory data analysis is a type of process that performs initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization, such as box plots, histograms, scatter plots, etc. Exploratory data analysis can be used to understand and summarize the data, as well as to generate hypotheses or questions for further analysis or research. For example, exploratory data analysis can be used to identify and visualize the characteristics, features, or behaviors of the data, as well as to measure their distribution, frequency, or correlation. The other options are not types of processes that perform initial investigations on data to spot outliers, discover patterns, and test assumptions with statistical insight and graphical visualization. Here is what they mean:
A t-test is a type of statistical method that tests whether there is a significant difference between the means of two groups or samples, such as whether there is a difference between the average exam scores of two classes in this case. A t-test can be used to test or verify a claim or an assumption about the data, as well as to measure the confidence or the error of the estimation.
A performance analysis is a type of process that measures whether the data meets certain goals or objectives, such as targets, benchmarks, or standards. A performance analysis can be used to identify and visualize the gaps, deviations, or variations in the data, as well as to measure the efficiency, effectiveness, or quality of the outcomes. For example, a performance analysis can be used to determine if there is a gap between a student's test score and their expected score based on their previous performance.
A link analysis is a type of process that determines whether the data is connected to other datapoints, such as entities, events, or relationships. A link analysis can be used to identify and visualize the patterns, networks, or associations among the datapoints, as well as to measure the strength, direction, or frequency of the connections. For example, a link analysis can be used to determine if there is a connection between a customer's purchase history and their loyalty program status.

291. Frage
An analyst runs a report on a daily basis, and the number of datapoints must be validated before the data can be analyzed. The number of datapoints increases each day by approximately 20% of the total number from the day before. On a given day, the number of datapoints was 8,798. Which of the following should be the total number of datapoints on the next day?

• A. 10,600
• B. 10,800
• C. 9,600
• D. 7,038

Antwort: A

Begründung:
This is because the number of datapoints increases each day by approximately 20% of the total number from the day before. Therefore, to find the number of datapoints on the next day, we can use the formula:

Plugging in the given values, we get:

Since we are dealing with whole numbers, we can round up the result to the nearest integer, which is 10,600.

292. Frage
Given the following customer and order tables:
Which of the following describes the number of rows and columns of data that would be present after performing an INNER JOIN of the tables?

• A. Nine rows, five columns
• B. Seven rows, eight columns
• C. Eight rows, seven columns
• D. Five rows, eight columns

Antwort: B

Begründung:
Explanation
This is because an INNER JOIN is a type of join that combines two tables based on a matching condition and returns only the rows that satisfy the condition. An INNER JOIN can be used to merge data from different tables that have a common column or a key, such as customer ID or order ID. To perform an INNER JOIN of the customer and order tables, we can use the following SQL statement:

This statement will select all the columns (*) from both tables and join them on the customer ID column, which is the common column between them. The result of this statement will be a new table that has seven rows and eight columns, as shown below:

The reason why there are seven rows and eight columns in the result table is because:
There are seven rows because there are six customers and six orders in the original tables, but only five customers have matching orders based on the customer ID column. Therefore, only five rows will have data from both tables, while one row will have data only from the customer table (customer 5), and one row will have no data at all (null values).
There are eight columns because there are four columns in each of the original tables, and all of them are selected and joined in the result table. Therefore, the result table will have four columns from the customer table (customer ID, first name, last name, and email) and four columns from the order table (order ID, order date, product, and quantity).

293. Frage
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. Cluster
• B. Stratified
• C. Simple random
• D. Systematic

Antwort: B

Begründung:
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.

294. Frage
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.

Antwort:

Begründung:
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.

295. Frage
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