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Questions and Answers
An iterative cycle of questioning and visualization is essential in EDA.
An iterative cycle of questioning and visualization is essential in EDA.
True
A goal of EDA is to understand relationships and patterns in data without fitting a statistical model.
A goal of EDA is to understand relationships and patterns in data without fitting a statistical model.
True
One purpose of EDA is to detect missing values and data quality issues.
One purpose of EDA is to detect missing values and data quality issues.
True
EDA focuses solely on numerical data, ignoring categorical data.
EDA focuses solely on numerical data, ignoring categorical data.
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Data frames in R allow each row to represent an observation and each column to represent a variable.
Data frames in R allow each row to represent an observation and each column to represent a variable.
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The dim() function in R returns the dimensions of a data frame in terms of rows and columns.
The dim() function in R returns the dimensions of a data frame in terms of rows and columns.
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The str() function provides an overview of the contents and structure of a data frame.
The str() function provides an overview of the contents and structure of a data frame.
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A data frame must only contain numerical data for analysis in R.
A data frame must only contain numerical data for analysis in R.
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The summary() function in R provides a quick overview of summary statistics for each column in a data frame.
The summary() function in R provides a quick overview of summary statistics for each column in a data frame.
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The dplyr package is a part of the tidyverse collection of R packages.
The dplyr package is a part of the tidyverse collection of R packages.
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