DA0-001 Online Practice Questions and Answers

Correct Answer: A

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.

Correct Answer: AB

Explanation: The reasons to create and maintain a data dictionary are to improve data acquisition and to remember specifics about data fields. A data dictionary is a document or a database that describes the structure, meaning, and usage of the data elements in a data source or a database. A data dictionary can help to improve data acquisition by providing clear and consistent definitions, rules, and standards for the data collection process. A data dictionary can also help to remember specifics about data fields by providing information such as data type, format, length, range, default value, constraints, relationships, etc. The other options are not reasons to create and maintain a data dictionary, as they are related to other aspects of data management or security. A data dictionary does not specify user groups for databases, as this is a function of access control or authorization. A data dictionary does not provide continuity through personnel turnover, as this is a function of documentation or knowledge transfer. A data dictionary does not confine breaches of PHI data, as this is a function of encryption or anonymization. A data dictionary does not reduce processing power requirements, as this is a function of optimization or compression. Reference: [What is a Data Dictionary? - DataCamp]

Correct Answer: D

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:

Correct Answer: D

Explanation: The invalid data type is the best description for the issue in which character values are mixed with integer values in a data set column. Invalid data type means that the data does not match the expected or required format or structure for a given variable or attribute. For example, if a column is supposed to store numerical values, but some rows contain text values, then those rows have an invalid data type. References: CompTIA Data+ Certification Exam Objectives, page 10

Correct Answer: D

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 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 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.

Correct Answer: B

Explanation: The mean height for the five dogs is 405mm. The mean, or average, is a measure of central tendency that represents the sum of all values divided by the number of values. To calculate the mean height for the five dogs, we can

use the following formula:

Mean = (300 + 430 + 170 + 470 + 600) / 5 = 2020 / 5 = 404 We can round up the result to the nearest millimeter, which is 405mm. The other options are not correct, as they are either too high or too low than the actual mean. Reference:

[Mean - Math is Fun]

Correct Answer: D

Explanation: This is because data encryption is a type of control measure that prevents a data breach, which is an unauthorized or illegal access or use of data by an external or internal party. Data encryption can prevent a data breach by protecting and securing the data using a code or a key that scrambles or transforms the data into an unreadable or incomprehensible format, which can only be decoded or restored by authorized users who have the correct code or key. For example, data encryption can prevent a data breach by encrypting the data in transit or at rest, such as when the data is sent over a network or stored in a device. The other control measures are not used for preventing a data breach. Here is why:

Data transmission is a type of process that transfers and exchanges data between different sources or systems, such as databases, cloud services, or web applications. Data transmission does not prevent a data breach, but rather exposes the data to potential risks or threats during the transfer or exchange. However, data transmission can be made more secure and less vulnerable to a data breach by using encryption or other methods, such as authentication or authorization. Data attribution is a type of feature or function that assigns and tracks the ownership and origin of the data, such as the creator, modifier, or source of the data. Data attribution does not prevent a data breach but rather provides information and evidence about the data provenance and history. However, data attribution can be useful for detecting and responding to a data breach by using audit logs or metadata to identify and trace any unauthorized or illegal access or use of the data. Data retention is a type of policy or standard that specifies and regulates the storage and preservation of the data, such as the duration, location, or format of the data. Data retention does not prevent a data breach, but rather affects the availability and accessibility of the data for future use or reference. However, data retention can be optimized and aligned with the legal and ethical requirements and standards of the industry or the organization to reduce the risk or impact of a data breach.

Correct Answer: D

Explanation: Python is a common data analytics tool that is also used as an interpreted, high-level, general-purpose programming language. Python has a simple and expressive syntax that makes it easy to read and write code. Python also has a rich set of libraries and frameworks that support various tasks and applications in data analytics, such as data manipulation, visualization, machine learning, natural language processing, web scraping, and more. Some examples of popular Python libraries for data analytics are pandas, numpy, matplotlib, seaborn, scikit-learn, nltk, and beautifulsoup. Python is different from other data analytics tools that are not programming languages but rather software applications or platforms that provide graphical user interfaces (GUIs) for data analysis and visualization. Some examples of these tools are SAS, Microsoft Power BI, IBM SPSS. Therefore, the correct answer is D. References: [What is Python? | Definition and Examples], [Python Libraries for Data Science]

Correct Answer: A

Explanation: The answer is A. Outlier.

Short explanation: An outlier is a data point that differs significantly from the rest of the data in a dataset. An outlier can indicate an error, an anomaly, or a rare event in the data. An outlier can affect the statistical analysis and visualization of

the data, such as skewing the mean, variance, or distribution of the data. Therefore, data should be cleaned to identify and remove or correct any outliers.

The image below shows a box plot graph with a vertical axis labeled "Customer Calls" and a horizontal axis labeled "Churn". The box plot is blue in color and the median value is around 2. There are 7 outliers above the box plot, ranging from

4 to 8.

image)

A box plot is a type of graph that can show the distribution of data values using five summary statistics: minimum, maximum, median, first quartile, and third quartile. The box represents the interquartile range (IQR), which is the difference

between the first and third quartiles. The median is shown as a line inside the box. The whiskers extend from the box to the minimum and maximum values, excluding any outliers. Outliers are shown as dots or circles outside the whiskers.

In this graph, we can see that most of the customer calls are between 0 and 4, with a median of 2. However, there are 7 outliers that have more than 4 customer calls, up to 8. These outliers may indicate some customers who have more

issues or complaints than others, or some errors or anomalies in the data collection or recording process. These outliers can affect the analysis and interpretation of the customer calls and churn relationship, such as making it seem that more

customer calls lead to less churn, which may not be true for the majority of the customers. Therefore, data should be cleaned to investigate and handle these outliers appropriately.

Correct Answer: A