DA0-001 Torrent - DA0-001 Valid Test Vce
DA0-001 Torrent - DA0-001 Valid Test Vce
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CompTIA Data+ Certification Exam Sample Questions (Q63-Q68):
NEW QUESTION # 63
Which of the following is an example of structured data?
- A. Social media correspondence
- B. A credit card number
- C. An email
- D. A photo
Answer: B
Explanation:
A credit card number is an example of structured data, which is a type of data that conforms to a data model, has a well-defined structure, follows a consistent order, and can be easily accessed and used by a person or a computer program. A credit card number consists of 16 digits that are divided into four groups of four digits each, separated by spaces or hyphens. The first six digits indicate the issuer identification number, the next nine digits indicate the account number, and the last digit is a check digit that validates the number. A credit card number can be stored and processed in a structured format, such as a database or a spreadsheet1.
NEW QUESTION # 64
A data analyst has been asked to derive a new variable labeled "Promotion_flag" based on the total quantity sold by each salesperson. Given the table below:
Which of the following functions would the analyst consider appropriate to flag "Yes" for every salesperson who has a number above 1,000,000 in the Quantity_sold column?
- A. Date
- B. Logical
- C. Aggregate
- D. Mathematical
Answer: B
NEW QUESTION # 65
A county in Illinois is conducting a survey to determine the mean annual income per household. The county is
427sq mi (2.65q km). Which of the following sampling methods would MOST likely result in a representative sample?
- A. A systematic survey that is sent to 100 single-family homes in the county
- B. A stratified phone survey of 100 people that is conducted between 2:00 p.m. and 3:00 p.m.
- C. Surveys sent to ten randomly selected homes within 5mi (8km) of the county's office
- D. Surveys sent to 100 randomly selected homes that are reflective of the population
Answer: D
Explanation:
Explanation
Surveys sent to 100 randomly selected homes that are reflective of the population. This is because a random sample is a type of sample that is selected by using a random method, such as a lottery or a computer-generated number, which ensures that every element in the population has an equal chance of being selected. A random sample can result in a representative sample, which means that the sample reflects the characteristics and diversity of the population. By sending surveys to 100 randomly selected homes that are reflective of the population, the analyst can ensure that the sample is representative of the county's households and their income levels. The other sampling methods are not likely to result in a representative sample. Here is why:
A stratified phone survey of 100 people that is conducted between 2:00 p.m. and 3:00 p.m. would result in a biased sample, which means that the sample favors or excludes certain groups or elements in the population.
By conducting the survey only between 2:00 p.m. and 3:00 p.m., the analyst would miss out on people who are not available or reachable at that time, such as those who are working or sleeping. This could affect the representativeness and generalizability of the sample.
A systematic survey that is sent to 100 single-family homes in the county would result in an unrepresentative sample, which means that the sample does not reflect the characteristics and diversity of the population. By sending surveys only to single-family homes, the analyst would ignore other types of households, such as apartments, condos, or mobile homes. This could affect the accuracy and reliability of the sample.
Surveys sent to ten randomly selected homes within 5mi (8km) of the county's office would result in a small sample, which means that the sample size is too low to capture the variability and diversity of the population.
By sending surveys only to ten homes within a limited area, the analyst would miss out on many households that are located in different parts of the county. This could affect the precision and confidence of the sample.
NEW QUESTION # 66
Which of the following query optimization techniques involves examining only the data that is needed for a particular task?
- A. Indexing documents
- B. Creating an execution plan
- C. Creating a flat file
- D. Making a temporary table
Answer: A
Explanation:
The correct answer is C. Indexing documents.
Indexing documents is a query optimization technique that involves creating a data structure that allows faster access to the data in the documents. Indexing documents can reduce the amount of data that needs to be scanned for a particular query, thus improving the performance and efficiency of the query. Indexing documents can also help with searching, sorting, filtering, and aggregating the data in the documents12
NEW QUESTION # 67
A data analyst who works for a government agency is required to obtain the average income of citizens. The list of citizens is given in the following table:
A value for one citizen's income is missing. Which of the following approaches should the data analyst take to solve this issue?
- A. Replace the missing value with the average of the rest of the unemployed citizens.
- B. Impute the mean of the other citizens' incomes into the field with the missing value.
- C. Exclude employed citizens from the analysis.
- D. Insert the value 0 into the field with the missing value.
Answer: B
Explanation:
Comprehensive and Detailed In-Depth Explanation:
Handling missing datais crucial for maintaining the integrity of an analysis. Since the missing value belongs to anemployedindividual, the most appropriate method is toimpute the mean income of employed citizens.
* Option A (Replace the missing value with the average of unemployed citizens):Incorrect. The missing income is for anemployedindividual, so it would be inappropriate to use the unemployed citizens' average.
* Option B (Insert 0):Incorrect. Assigning 0 would be misleading since it does not reflect the income distribution for employed citizens.
* Option C (Impute the mean of the other citizens' incomes):Correct.A common practice in data analytics ismean imputation, where missing values are replaced with the mean of similar cases (in this case, other employed citizens).
* Option D (Exclude employed citizens from the analysis):Incorrect. This would remove valuable data and lead to biased results.
NEW QUESTION # 68
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