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CompTIA Data+ Certification Exam Sample Questions (Q307-Q312):

NEW QUESTION # 307
Given the following data table:

Which of the following are appropriate reasons to undertake data cleansing? (Select two).

A. Duplicate data
B. Invalid data
C. Redundant data
D. Missing data
E. Non-parametric data
F. Normalized data

Answer: B,D

Explanation:
Data cleansing is a critical process in data analytics to ensure the accuracy and quality of data. The reasons to undertake data cleansing include:
Missing Data (B): Missing data can lead to incomplete analysis and biased results. It is essential to identify and address gaps in the dataset to maintain the integrity of the analysis1.
Invalid Data (D): Invalid data includes entries that are out of range, improperly formatted, or illogical (e.g., a negative age). Such data can corrupt analysis and lead to incorrect conclusions1.
Other options, such as non-parametric data (A), are not inherently errors but refer to a type of data that doesn't assume a normal distribution. Duplicate data and redundant data (E) could also be reasons for data cleansing, but they are not listed as options to select from in the provided image details. Normalized data (F) refers to data that has been processed to fit into a certain range or format and is typically not a reason for data cleansing.
Reference:
Understanding the importance of data quality and the impacts of missing and invalid data on research outcomes1.
Best practices in data cleansing2.
Data cleansing is required for various reasons, two of which are missing data (B) and invalid data (D). From the table provided, we can infer the necessity of cleansing in the context of ensuring data integrity and consistency. Missing data refers to the absence of data where it is expected, which can hinder analysis due to incomplete information. Invalid data refers to data that is incorrect, out of range, or in an inappropriate format, which can lead to inaccuracies in any analysis or report. Both these issues can significantly affect the outcomes of any data-related operations and thus need to be rectified through the data cleansing process.

NEW QUESTION # 308
A data analyst has received a data set that contains actual and projected sales for the fourth quarter of 2019. Which of the following statistical methods should the analyst use to find the measure of dispersion?

A. Variance
B. Confidence interval
C. Correlation
D. Mean

Answer: A

Explanation:
The measure of dispersion is used to describe the spread of data around a central value. In the context of a data set containing actual and projected sales, the measure of dispersion will help to understand the variability or consistency of sales figures. The variance is themost appropriate statistical method for finding the measure of dispersion because it calculates the average of the squared differences from the Mean, providing a clear picture of data spread. It is especially useful in comparing the spread between different data sets and understanding the distribution of data points.
Mean is a measure of central tendency, not dispersion.
Correlation measures the relationship between two variables, not the spread of a single variable.
Confidence intervals are used to estimate the range within which a population parameter will fall, but they do not measure dispersion within the data set itself.
Reference:
Measures of Dispersion in Statistics1
Measures of Dispersion - Definition, Formulas, Examples2
Statistical dispersion - Wikipedia3

NEW QUESTION # 309
Given the data below:

In which of the following file formats is the data presented?

A. Xs
B. CSV
C. RIF
D. XML

Answer: B

Explanation:
The data is presented in a CSV (comma-separated values) file format, which is a plain text format that stores tabular data. Each line of the file is a data record, and each record consists of one or more fields separated by commas. The first line of the file usually contains the names of the fields, also known as the header. In this case, the data has four fields: Name, Age, Gender, and Occupation. Therefore, the correct answer is B. Reference: CSV File (What It Is & How to Open One), Comma-separated values - Wikipedia

NEW QUESTION # 310
The duration of a phone call in milliseconds is an example of:

A. boolean data.
B. nominal data.
C. continuous data.
D. ordinal data.

Answer: C

Explanation:
Explanation
The correct answer is D. Continuous data.
Continuous data is a type of quantitative data that can take any value within a range and can be measured with infinite precision. Continuous data can be expressed as fractions, decimals, or percentages. Examples of continuous data are height, weight, temperature, time, speed, etc12 The duration of a phone call in milliseconds is an example of continuous data, because it can take any value within a range (from zero to infinity) and can be measured with infinite precision (up to milliseconds or even smaller units). The duration of a phone call in milliseconds can also be expressed as fractions, decimals, or percentages of a larger unit (such as seconds, minutes, or hours).
Ordinal data is not correct, because ordinal data is a type of qualitative or categorical data that can be ordered or ranked according to some criterion. Ordinal data can have a logical order, but the intervals between the values are not equal or meaningful. Examples of ordinal data are grades, ratings, ranks, etc12 Nominal data is not correct, because nominal data is a type of qualitative or categorical data that can be labeled or named without any order or ranking. Nominal data can have a finite number of categories or classes, but the categories have no intrinsic value or hierarchy. Examples of nominal data are gender, color, nationality, etc12 Boolean data is not correct, because boolean data is a type of binary data that can have only two possible values: true or false. Boolean data can be used to represent logical statements, conditions, or outcomes.
Examples of boolean data are yes/no, on/off, 1/0, etc.

NEW QUESTION # 311
A data analyst has been asked to create an ad-hoc sales report for the Chief Executive Officer (CEO).
Which of the following should be included in the report?

A. YTD total sales.
B. Line-item SKU numbers.
C. The customers' first and last names.
D. The sales representatives' home addresses.

Answer: A

Explanation:
The report for the CEO should include YTD total sales, as this will provide a high-level overview of the sales performance of the company and show how it is meeting its annual goals. The other options are not appropriate for the CEO, as they are either too detailed or irrelevant for the report. The sales representatives' home addresses, line-item SKU numbers, and customers' first and last names are not related to the sales performance and might compromise the privacy and security of the data. Reference: CompTIA Data+ (DA0-
001) Practice Certification Exams | Udemy

NEW QUESTION # 312
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