Question # 1
You are working with a dataset and need to swap the values in rows with those in columns.
What action do you need to perform? | A. Recording | B. Filtering | C. Aggregation | D. Transposition |
D. Transposition
Explanation:
Transpose creates a new data file in which the rows and columns in the original data file are transposed so that cases (rows) become variables and variables (columns) become cases. Transpose automatically creates new variable names and displays a list of the new variable names.
Transposing data is useful for data analysis. At times, we have to pull data from various files with different formats for analysis and preparing reports. In such circumstances, we may have to transpose some data from one file to the other. In excel, we can transpose data in multiple ways.
Question # 2
Which of the following is a difference between a primary key and a unique key?
| A. A unique key cannot take null values, whereas a primary key can take null values.
| B. There can be only one primary key in a data set, whereas there can be multiple unique keys.
| C. A primary key can take a value more than once, whereas a unique key cannot take a value more than once.
| D. A primary key cannot be a date variable, whereas a unique key can be.
|
B. There can be only one primary key in a data set, whereas there can be multiple unique keys.
Explanation:
The correct answer is B. There can be only one primary key in a data set, whereas there can be multiple unique keys.
A primary key is a column or a set of columns that uniquely identifies each row in a table. A table can have only one primary key, which also enforces the NOT NULL constraint on the column(s) involved. A primary key can also be referenced by a foreign key of another table to establish a relationship between the tables.
A unique key is a column or a set of columns that also uniquely identifies each row in a table, but it is not the primary key. A table can have more than one unique key, which also allows one NULL value for the column(s) involved. A unique key can also be referenced by a foreign key of another table to establish a relationship between the tables.
Some of the differences between a primary key and a unique key are:
A primary key creates a clustered index on the column(s), whereas a unique key creates a non-clustered index on the column(s).
A primary key does not allow any NULL values, whereas a unique key allows one NULL value for the column(s).
A primary key can be a unique key, but a unique key cannot be a primary key.
Question # 3
Which one of the following programming languages is specifically designed for use in analytics applications?
| A. Python | B. R | C. C++ | D. Java |
B. R
Question # 4
Which of the following best describes a business analytics tool with interactive visualization and business capabilities and an interface that is simple enough for end users to create their own reports and dashboards? | A. Python | B. R | C. Microsoft Power Bl
| D. SAS |
C. Microsoft Power Bl
Explanation:
The best answer is C. Microsoft Power BI.
Microsoft Power BI is a business analytics and business intelligence service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. Power BI can connect to multiple data sources, clean and transform data, create custom calculations, and visualize data through charts, graphs, and tables. Power BI can be accessed through a web browser, mobile device, or desktop application and integrated with other Microsoft tools like Excel and SharePoint12.
Python is not correct, because Python is a general-purpose programming language that can be used for various applications, including data analysis and visualization. However, Python is not a dedicated business analytics tool, and it requires coding or programming skills to create reports and dashboards.
R is not correct, because R is a programming language and software environment for statistical computing and graphics. R can be used for data analysis and visualization, but it is not a specialized business analytics tool, and it requires coding or programming skills to create reports and dashboards.
SAS is not correct, because SAS is a software suite for advanced analytics, business intelligence, data management, and predictive analytics. SAS can provide interactive visualizations and business capabilities, but it does not have an interface that is simple enough for end users to create their own reports and dashboards. SAS also requires coding or programming skills to use its features.
Question # 5
Which of the following is an example of a flat file?
| A. CSV file
| B. PDF file
| C. JSON file
| D. JPEG file
|
A. CSV file
Explanation:
A CSV file is a type of flat file that stores data as plain text in a table-like structure with rows and columns. Each row represents a single record, while columns represent fields or attributes of the data. A CSV file uses commas or other delimiters to separate the values in each row. A CSV file can be easily imported or exported by various applications and programs.
Question # 6
Which of the following data manipulation techniques should an analyst use to hide unnecessary data during analysis? | A. Filtering | B. Parametrization | C. Sorting | D. Indexing |
A. Filtering
Question # 7
A customer survey reveals 90% positive feedback. Which of the following statistical methods would be best to utilize to determine the reliability of a data set and predict how a larger sample of customers over the same time period might respond? | A. Calculate a high variance on survey responses.
| B. Calculate the maximum range of the survey responses.
| C. Calculate a low standard deviation on survey responses.
| D. Remove any data more than 4 standard deviation from the mean.
|
C. Calculate a low standard deviation on survey responses.
Explanation:
A low standard deviation in survey responses indicates that the data points tend to be close to the mean, suggesting a high level of consistency among the responses. This consistency is crucial for determining the reliability of the data set and predicting future outcomes. If the standard deviation is low, it means that the positive feedback is not only high but also consistent, making it a reliable indicator of customer satisfaction and a good predictor of how a larger sample might respond.
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