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CompTIA Data+ Certification Exam Sample Questions (Q22-Q27):

NEW QUESTION # 22
An analyst is designing a dashboard to determine which site has the highest percentage of new customers. 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 to BEST display the data?

Answer: C

Explanation:
This is because 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 the percentage of new customers for different sites 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 site has the highest or lowest percentage of new customers, as well as show how much each site contributes to the total percentage of new customers. The other types of charts are not the best charts to display the data. Here is why:
* A line chart is a type of chart that shows the change or the trend of a single variable over time, such as the percentage of new customers over months or years in this case. A line chart can be used to display and analyze the movement, cycle, or pattern of the variable, as well as identify any peaks, valleys, or fluctuations in the data. For example, a line chart can show how the percentage of new customers increases or decreases over time, as well as show if there are any seasonal or periodic variations in the data.
* A pie chart is a type of chart that shows the proportion or the percentage of a single variable for different categories or groups, such as the percentage of new customers for different sites in this case. A pie chart can be used to display and analyze the composition, distribution, or share of the variable, as well as identify any segments, slices, or fractions in the data. For example, a pie chart can show how much each site represents of the total percentage of new customers, as well as show if there are any dominant or minor sites in the data.
* A scatter chart is a type of chart that shows the relationship between two variables for each observation or unit in a data set, such as the percentage of new customers and another variable for each site in this case. A scatter chart 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 chart can show if there is a positive, negative, or no correlation between the percentage of new customers and another variable, such as sales revenue or customer satisfaction.


NEW QUESTION # 23
In a tabular dataset, what term is used to describe the data that appears in a single row?

Answer: D


NEW QUESTION # 24
A data analyst wants to create "Income Categories" that would be calculated based on the existing variable "Income". The "Income Categories" would be as follows:
Income category 1: less than $1.
Income category 2: more than $1 and less than $20,000.
Income category 3: more than $20,001 and less than $40,000.
Income category 4: more than $40,001.
Which of the following data manipulation techniques should the data analyst use to create "Income Categories"?

Answer: C

Explanation:
The correct answer is B: Derived variables Derived variables are variables that you create by calculating or categorizing variables that already exist in your data set.
Data merge is incorrect. Data merging is the process of combining two or more data sets into a single data set. Data blending is incorrect.
Data blending involves pulling data from different sources and creating a single, unique, dataset for visualization and analysis.
Data append is incorrect. A data append is a process that involves adding new data elements to an existing database.


NEW QUESTION # 25
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?

Answer: B

Explanation:
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.


NEW QUESTION # 26
An analyst needs to join two tables of data together for analysis. All the names and cities in the first table should be joined with the corresponding ages in the second table, if applicable.

Which of the following is the correct join the analyst should complete. and how many total rows will be in one table?

Answer: D

Explanation:
Explanation
The correct join the analyst should complete is B. LEFT JOIN, four rows.
A LEFT JOIN is a type of SQL join that returns all the rows from the left table, and the matched rows from the right table. If there is no match, the right table will have null values. A LEFT JOIN is useful when we want to preserve the data from the left table, even if there is no corresponding data in the right table1 Using the example tables, a LEFT JOIN query would look like this:
SELECT t1.Name, t1.City, t2.Age FROM Table1 t1 LEFT JOIN Table2 t2 ON t1.Name = t2.Name; The result of this query would be:
Name City Age Jane Smith Detroit NULL John Smith Dallas 34 Candace Johnson Atlanta 45 Kyle Jacobs Chicago 39 As you can see, the query returns four rows, one for each name in Table1. The name John Smith appears twice in Table2, but only one of them is matched with the name in Table1. The name Jane Smith does not appear in Table2, so the age column has a null value for that row.


NEW QUESTION # 27
......

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