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The CompTIA DA0-001 certification from CompTIA is a sought-after recognition of TestKingIT skills and knowledge. With this CompTIA Data+ Certification Exam certification, professionals can enhance their careers, boost earnings, and showcase their expertise in a competitive job market. The benefits of passing the DA0-001 Exam are numerous, but preparing for the exam is not a simple feat.
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CompTIA Data+ certification exam also tests the candidate's ability to use various data management software and tools such as Microsoft Excel, Access, and SQL. Additionally, it emphasizes the importance of data security, and it focuses on the best practices for protecting sensitive information. Therefore, candidates who are appearing for this certification have to be familiar with various data protection mechanisms and strategies.
Mining data
Applying basic statistical methods
Visualizing and reporting data
Manipulating data
Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
NEW QUESTION # 302
Which of following is a non-relational database?
Answer: B
Explanation:
Neo4j is a type of non-relational database that uses a graph model to store dat a. A graph database is a database that represents data as nodes and edges, where nodes are entities and edges are relationships between them. A graph database can store complex and diverse data that is not easily structured in tables. A graph database can also perform fast and efficient queries on the data by traversing the connections between the nodes
NEW QUESTION # 303
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?
Answer: A
Explanation:
Explanation
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.
NEW QUESTION # 304
Which of the following are reasons to conduct data cleansing? (Select two).
Answer: A,E
Explanation:
Two reasons to conduct data cleansing are:
To improve accuracy: Data cleansing helps to ensure that the data is correct, consistent, and reliable. This can improve the quality and validity of the analysis, as well as the decision-making and outcomes based on the data12 To calculate trends: Data cleansing helps to remove or resolve any errors, outliers, or missing values that could distort or skew the dat a. This can help to identify and measure the patterns, changes, or relationships in the data over time13
NEW QUESTION # 305
Which of the following is the correct data type for text?
Answer: D
Explanation:
The correct data type for text is string. A string is a data type that represents a sequence of characters, such as letters, numbers, symbols, or spaces. A string can be enclosed by single quotes (' ') or double quotes (" ") in most programming languages. For example, 'Hello', "World", and "123" are all strings. The other options are not data types for text, but for other kinds of values. A boolean is a data type that represents a logical value, either true or false. An integer is a data type that represents a whole number, such as 1, 0, or -5. A float is a data type that represents a number with a fractional part, such as 3.14, 0.5, or -2.7. Reference: Data Types - W3Schools
NEW QUESTION # 306
An e-commerce company recently tested a new website layout. The website was tested by a test group of customers, and an old website was presented to a control group. The table below shows the percentage of users in each group who made purchases on the websites:
Which of the following conclusions is accurate at a 95% confidence interval?
Answer: B
Explanation:
The p-value is a measure of how likely it is to observe a difference in conversion rates as large or larger than the one observed, assuming that there is no difference between the groups. A common threshold for statistical significance is 0.05, meaning that there is a 5% or less chance of observing such a difference by chance alone.
The table shows the p-values for each country, and we can see that only Germany has a p-value above 0.05 (0.13). This means that we cannot reject the null hypothesis that there is no difference in conversion rates between the test and control groups in Germany. Therefore, the increase in conversion from the new layout was not significant in Germany. For the other countries, the p-values are below 0.05, indicating that the increase in conversion from the new layout was statistically significant. Option A is correct.
Option B is incorrect because the increase in conversion from the new layout was significant in France (p- value = 0.002).
Option C is incorrect because it does not account for the variation across countries. While the overall conversion rate for the test group (8.4%) is higher than the control group (6.8%), this difference may not be statistically significant when we consider the country-specific effects.
Option D is incorrect because the new layout has the highest conversion rate in the United Kingdom (9.6%), not the lowest.
References:
* P-value Calculator & Statistical Significance Calculator
* p-value Calculator | Formula | Interpretation
* How to obtain the P value from a confidence interval | The BMJ
* Confidence Intervals &P-values for Percent Change / Relative Difference
NEW QUESTION # 307
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