VALID REAL DA0-001 EXAM | DA0-001 TRAINING MATERIAL

Valid Real DA0-001 Exam | DA0-001 Training Material

Valid Real DA0-001 Exam | DA0-001 Training Material

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CompTIA Data+ Certification Exam Sample Questions (Q339-Q344):

NEW QUESTION # 339
Which of the following programming languages are best suited for analysis and machine-learning applications? (Select two).

  • A. Rust
  • B. Kotlin
  • C. R
  • D. PHP
  • E. Python
  • F. Ruby

Answer: C,E


NEW QUESTION # 340
A customer list from a financial services company is shown below:

A data analyst wants to create a likely-to-buy score on a scale from 0 to 100, based on an average of the three numerical variables: number of credit cards, age, and income. Which of the following should the analyst do to the variables to ensure they all have the same weight in the score calculation?

  • A. Recode the variables.
  • B. Calculate the standard deviations of the variables.
  • C. Normalize the variables.
  • D. Calculate the percentiles of the variables.

Answer: C

Explanation:
Explanation
Normalizing the variables means scaling them to a common range, such as 0 to 1 or -1 to 1, so that they have the same weight in the score calculation. Recoding the variables means changing their values or categories, which would alter their meaning and distribution. Calculating the percentiles of the variables means ranking them relative to each other, which would not account for their actual magnitudes. Calculating the standard deviations of the variables means measuring their variability, which would not make them comparable.
References: CompTIA Data+ Certification Exam Objectives, page 10


NEW QUESTION # 341
Which of the following is an example of a discrete variable?

  • A. The temperature of a hot tub
  • B. The time to complete a task
  • C. The number of people in an office
  • D. The height of a horse

Answer: C

Explanation:
Explanation
A discrete variable is a variable that can only take on a finite number of values, such as integers or categories.
The number of people in an office is an example of a discrete variable, as it can only be a whole number. The temperature of a hot tub, the height of a horse, and the time to complete a task are examples of continuous variables, as they can take on any value within a range. Reference: CompTIA Data+ (DA0-001) Practice Certification Exams | Udemy


NEW QUESTION # 342
You would like to measure how well an organization is achieving its goals.
What type of analysis should you perform?

  • A. Performance analysis.
  • B. Trend analysis.
  • C. Outlier analysis.
  • D. Predictive analysis.

Answer: A

Explanation:
Performance analysis is the technique of studying or comparing the performance of a specific situation in contrast to the aim and yet executed. In Human Resource, performance analysis can help to review an employee's contribution towards a project or assignment, which they allotted him or her.


NEW QUESTION # 343
A cereal manufacturer wants to determine whether the sugar content of its cereal has increased over the years.
Which of the following is the appropriate descriptive statistic to use?

  • A. Mean
  • B. Frequency
  • C. Percent change
  • D. Variance

Answer: C

Explanation:
This is because percent change is a type of descriptive statistic that measures the relative change or difference of a variable over time, such as the sugar content of cereal over years in this case. Percent change can be used to determine whether the sugar content of cereal has increased over years by comparing the initial and final values of the sugar content, as well as calculating the ratio or proportion of the change. For example, percent change can be used to determine whether the sugar content of cereal has increased over years by finding out how much more (or less) sugar there is in cereal now than before, as well as expressing it as a fraction or a percentage of the original sugar content. The other descriptive statistics are not appropriate to use to determine whether the sugar content of cereal has increased over years. Here is why:
* Frequency is a type of descriptive statistic that measures how often or how likely a value or an event occurs in a data set, such as how many times a certain sugar content appears in cereal in this case.
Frequency does not measure the relative change or difference of a variable over time, but rather measures the occurrence or chance of a variable at a given time.
* Variance is a type of descriptive statistic that measures how much the values in a data set vary or deviate from the mean or average of the data set, such as how much variation there is in sugar content among different cereals in this case. Variance does not measure the relative change or difference of a variable over time, but rather measures the dispersion or spread of a variable at a given time.
* Mean is a type of descriptive statistic that measures the average value or central tendency of a data set, such as what is the typical sugar content of cereal in this case. Mean does not measure the relative change or difference of a variable over time, but rather measures the summary or representation of a variable at a given time.


NEW QUESTION # 344
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