CompTIA DA0-001 Practice Test - Questions Answers, Page 16

The best type of chart to display the data is A. Include a bar chart using the site and the percentage of new customers data.

A bar chart is a good choice for comparing categorical data with numerical data, such as the site and the percentage of new customers. A bar chart can show the relative differences between the sites and highlight the site with the highest percentage of new customers. A bar chart can also be easily labeled and formatted to make the data clear and understandable.

A line chart is not suitable for this data, because it is used to show trends or changes over time, which is not relevant for the site and the percentage of new customers data. A line chart would also be confusing and misleading, as it would imply a connection or correlation between the sites that does not exist.

A pie chart is also not a good choice for this data, because it is used to show the proportion of a whole, not the comparison of different categories. A pie chart would also be difficult to read and interpret, as it would require labels or legends to identify the sites and their percentages. A pie chart would also not be able to show the exact values of the percentages, only their relative sizes.

A scatter chart is another inappropriate option for this data, because it is used to show the relationship or correlation between two numerical variables, not between a categorical and a numerical variable. A scatter chart would also be cluttered and unclear, as it would plot each site as a point on a coordinate plane, without any labels or axes. A scatter chart would also not be able to show the differences or rankings between the sites and their percentages.

The correct answer is B. There can be only one primary key in a data set, whereas there can be multiple unique keys.

A primary key is a column or a set of columns that uniquely identifies each row in a table. A table can have only one primary key, which also enforces the NOT NULL constraint on the column(s) involved.

A primary key can also be referenced by a foreign key of another table to establish a relationship between the tables12

A unique key is a column or a set of columns that also uniquely identifies each row in a table, but it is not the primary key. A table can have more than one unique key, which also allows one NULL value for the column(s) involved. A unique key can also be referenced by a foreign key of another table to establish a relationship between the tables12 Some of the differences between a primary key and a unique key are:

A primary key creates a clustered index on the column(s), whereas a unique key creates a nonclustered index on the column(s)3

A primary key does not allow any NULL values, whereas a unique key allows one NULL value for the column(s)123

A primary key can be a unique key, but a unique key cannot be a primary key12

The correct answer is

A) UNION ALL.

UNION ALL is a SQL statement that appends two tables that have the same number of columns and compatible data types. UNION ALL preserves all the rows from both tables, including any duplicates12

B) MERGE is not correct, because MERGE is a SQL statement that combines the data of two tables based on a common column. MERGE can perform insert, update, or delete operations on the target table depending on the matching or non-matching rows from the source table34

C) GROUP BY is not correct, because GROUP BY is a SQL clause that groups the rows of a table based on one or more columns. GROUP BY is often used with aggregate functions, such as SUM, AVG, COUNT, etc., to calculate summary statistics for each group56

D) JOIN is not correct, because JOIN is a SQL clause that combines the data of two tables based on a common column or condition. JOIN can produce different results depending on the type of join, such as INNER JOIN, LEFT JOIN, RIGHT JOIN, etc.

The correct answer is D. Spearman's rank correlation.

Spearman's rank correlation is a non-parametric test that measures the strength and direction of the relationship between two variables that are ranked (ordinal) or continuous. Spearman's rank correlation does not assume that the data follows a normal distribution or that the variables are linearly related. Spearman's rank correlation is based on the ranks of the data rather than the actual values12

A) One-sample t-test is not correct, because it is a parametric test that compares the mean of a sample to a specified value. One-sample t-test assumes that the data follows a normal distribution and has a known population standard deviation34

B) Two-way ANOVA is not correct, because it is a parametric test that compares the means of two or more groups that are influenced by two independent factors. Two-way ANOVA assumes that the data follows a normal distribution, has homogeneous variances, and has independent observations.

C) Correlation coefficient is not correct, because it is a parametric test that measures the strength and direction of the linear relationship between two continuous variables. Correlation coefficient assumes that the data follows a bivariate normal distribution and has no outliers.

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 glance1 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 report2

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 dashboard3

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.

The correct answer is A. 13.2%.

The total order conversion rate is the ratio of the total number of orders to the total number of clicks, expressed as a percentage. To calculate the total order conversion rate, we need to sum up the clicks and orders from all the channels, and then divide the orders by the clicks and multiply by 100.

Using the data from the table, we can do the following:

Total clicks = 580 + 800 + 1,200 + 300 + 620 = 3,500

Total orders = 55 + 100 + 220 + 60 + 85 = 520

Total order conversion rate = (520 / 3,500) x 100 = 14.857%

Rounding to one decimal place, we get 14.9%

Therefore, the total order conversion rate is 14.9%.

The best type of chart to display the data is D. Include a column chart using the site and sales to average sales per customer.

A column chart is a good choice for comparing categorical data with numerical data, such as the site and sales to average sales per customer. A column chart can show the relative differences between the sites and highlight the site with the highest sales volume per customer. A column chart can also be easily labeled and formatted to make the data clear and understandable.

A line chart is not suitable for this data, because it is used to show trends or changes over time, which is not relevant for the site and sales to average sales per customer dat a. A line chart would also be confusing and misleading, as it would imply a connection or correlation between the sites that does not exist.

A pie chart is also not a good choice for this data, because it is used to show the proportion of a whole, not the comparison of different categories. A pie chart would also be difficult to read and interpret, as it would require labels or legends to identify the sites and their sales to average sales per customer. A pie chart would also not be able to show the exact values of the sales to average sales per customer, only their relative sizes.

A scatter chart is another inappropriate option for this data, because it is used to show the relationship or correlation between two numerical variables, not between a categorical and a numerical variable. A scatter chart would also be cluttered and unclear, as it would plot each site as a point on a coordinate plane, without any labels or axes. A scatter chart would also not be able to show the differences or rankings between the sites and their sales to average sales per customer.

The correct answer is B. Transcription.

Transcription is a necessary step on the way to interpretation when a data set was recorded using multimedia technology. Multimedia technology refers to the use of various forms of media, such as audio, video, images, and text, to capture and present information1 Transcription is the process of converting multimedia data into written or textual form, which can then be analyzed using various methods and tools2 Transcription can help to make the data more accessible, searchable, and manageable, as well as to preserve the data for future use.

Structural equation modeling is not correct, because it is a statistical technique that tests the causal relationships between multiple variables using observed and latent variables. Structural equation modeling is not a necessary step on the way to interpretation, but rather an optional method that can be applied to certain types of data.

Sequential analysis is not correct, because it is a method of analyzing the order and timing of events or behaviors in a data set. Sequential analysis is not a necessary step on the way to interpretation, but rather an optional method that can be applied to certain types of data.

Sampling is not correct, because it is the process of selecting a subset of data from a larger population for analysis. Sampling is not a necessary step on the way to interpretation, but rather a preliminary step that can be done before collecting or analyzing the data.