DA0-001試験の準備方法｜有難いDA0-001テストトレーニング試験｜信頼的なCompTIA Data+ Certification Exam試験時間

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CompTIA Data+ Certification Exam 認定 DA0-001 試験問題 (Q387-Q392):

質問 # 387
A data analyst is attempting to understand how ice cream consumption is affected by different attributes. such as cost, temperature. and income level. Which of the following regression analyses should the data analyst perform to understand this relationship?

正解：B

解説：
answer: B. Ordinary least squares
Ordinary least squares (OLS) is a type of linear regression that is used to fit a regression model that describes the relationship between one or more predictor variables and a numeric response variable. Use when: The relationship between the predictor variable(s) and the response variable is reasonably linear. The response variable is a continuous numeric variable1.
In this case, the data analyst is interested in understanding how ice cream consumption (the response variable) is affected by different attributes, such as cost, temperature, and income level (the predictor variables).
Assuming that these variables have a linear relationship, OLS can be used to estimate the coefficients of the regression equation that best fits the data. OLS can also provide measures of goodness-of-fit, such as R- squared and adjusted R-squared, and test the significance of the coefficients using t-tests and F-tests2.
Option A is incorrect, as logistic regression is used to fit a regression model that describes the relationship between one or more predictor variables and a binary response variable. Use when: The response variable is binary - it can only take on two values1. Ice cream consumption is not a binary variable, but rather a continuous numeric variable.
Option C is incorrect, as Cox regression is used to fit a regression model that describes the relationship between one or more predictor variables and a survival time response variable. Use when: The response variable is the time until an event of interest occurs, such as death, failure, or recovery3. Ice cream consumption is not a survival time variable, but rather a continuous numeric variable.
Option D is incorrect, as polynomial regression is used to fit a regression model that describes the relationship between one or more predictor variables and a numeric response variable. Use when: The relationship between the predictor variable(s) and the response variable is non-linear1. If there is no evidence of non- linearity in the data, polynomial regression may not be appropriate, as it may overfit the data and produce unreliable estimates.


質問 # 388
Which of the following data types should an analyst use to provide the most flexibility when recording emails on a form?

正解：D

解説：
Comprehensive and Detailed In-Depth
When designing a form to record email addresses, selecting the appropriate data type is crucial to ensure data integrity and flexibility.
Alphanumeric: This data type allows for both letters and numbers. While email addresses do contain alphanumeric characters, they also include special symbols such as '@' and '.', which an alphanumeric data type might not support, leading to potential data entry issues.
Text: This data type is designed to handle a sequence of characters, including letters, numbers, and special symbols. It provides the most flexibility for email addresses, accommodating the full range of characters required.
Discrete: This refers to distinct, separate values, often numerical, and is not suitable for the variable nature of email addresses.
Continuous: This pertains to data that can take any value within a range, typically used for measurements, and is not applicable to email addresses.
Therefore, the 'Text' data type is the most appropriate choice for recording email addresses, as it accommodates all necessary characters without restrictions.
Reference:
CompTIA Partners


質問 # 389
A data analyst needs to present the results of an online marketing campaign to the marketing manager. The manager wants to see the most important KPIs and measure the return on marketing investment. Which of the following should the data analyst use to BEST communicate this information to the manager?

正解：D

解説：
Explanation
A summary with statistics, conclusions, and recommendations from the data analyst is the best way to communicate the results of an online marketing campaign to the marketing manager. A summary can provide a concise and clear overview of the most important KPIs and measure the return on marketing investment, as well as highlight the main findings and insights from the data analysis. A summary can also include actionable suggestions and best practices for improving the campaign performance and achieving the marketing objectives. A summary is different from other options, such as a real-time monitor, a self-service dashboard, or a spreadsheet of raw data, which may not provide enough context, interpretation, or guidance for the manager.
Therefore, the correct answer is D. References: How to Write a Data Analysis Report: 6 Essential Tips, How to Write a Marketing Report (with Pictures) - wikiHow


質問 # 390
An analyst must obtain the average daily sales for the following week:

Which of the following must the analyst perform to obtain this value?

正解：B

解説：
Data aggregation is the process of compiling data from multiple sources and summarizing it into a single dataset. Data aggregation can be used to calculate statistics, such as averages, sums, counts, or percentages. In this case, the analyst must obtain the average daily sales for the following week, which is a statistic that can be calculated by aggregating the sales data from each day and dividing by the number of days. Data aggregation can be done using various tools and methods, such as spreadsheets, databases, or programming languages.


質問 # 391
An analyst must obtain the average daily sales for the following week:

Which of the following must the analyst perform to obtain this value?

正解：B

解説：
Explanation
Data aggregation is the process of compiling data from multiple sources and summarizing it into a single dataset. Data aggregation can be used to calculate statistics, such as averages, sums, counts, or percentages. In this case, the analyst must obtain the average daily sales for the following week, which is a statistic that can be calculated by aggregating the sales data from each day and dividing by the number of days. Data aggregation can be done using various tools and methods, such as spreadsheets, databases, or programming languages.


質問 # 392
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