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Look at the dataset below, called df. Which of the following codes would return either or both of the mean and sample standard deviation of the column magnitude? You can assume that the tidyverse package is loaded. Click all that apply. Group of answer choices

Look at the dataset below, called df. Which of the following codes would return either or both of the mean and sample standard deviation of the column magnitude? You can assume that the tidyverse package is loaded. Click all that apply. Group of answer choices

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Look at the dataset below, called df. Which of the following codes would return either or both of the mean and sample standard deviation of the column magnitude?    You can assume that the tidyverse package is loaded. Click all that apply.
Group of answer choices
 
The image contains a list of code snippets related to data summarization and descriptive statistics, typically used in the R programming language. Each snippet is framed in a box with rounded corners. ### Code Snippets: 1. **df %>% summarise(mean = mean(magnitude), sd = sd(magnitude))** - Explanation: This code uses the `summarise()` function from the `dplyr` package to calculate the mean and standard deviation (`sd`) of the `magnitude` column in the dataframe `df`. 2. **mean(df$magnitude)** - Explanation: This code calculates the mean of the `magnitude` column in the dataframe `df` using the base R function `mean()`. 3. **sd(df$magnitude)** - Explanation: This code calculates the standard deviation of the `magnitude` column in the dataframe `df` using the base R function `sd()`. 4. **df %>% descriptive(magnitude)** - Explanation: This code appears to be an attempt to use the `descriptive()` function (potentially from a specific package) on the `magnitude` column in the dataframe `df`. However, this function is not a standard function in base R or commonly used packages, suggesting this may be pseudo-code or illustrative. 5. **descriptive(df$magnitude)** - Explanation: Similar to the previous snippet, this code also attempts to use the `descriptive()` function directly on the `magnitude` column of the dataframe `df`. This function name suggests it would provide general descriptive statistics, but it is not standard in base R. 6. **df %>% summarise(mean = magnitude, sd = magnitude)** - Explanation: This code is incorrect as `mean = magnitude` and `sd = magnitude` imply the `magnitude` is already summarized, which doesn't perform any statistical calculation. It should involve functions like `mean()` and `sd()` instead. ### Notes: - The `%>%` operator is known as the pipe operator in the `dplyr` package of R, used to chain operations. - The data frame `df` is used consistently in all snippets for demonstration purposes. - Only the first, second, and third snippets are syntactically correct and meaningful in R for calculating descriptive statistics.
Transcribed Image Text:The image contains a list of code snippets related to data summarization and descriptive statistics, typically used in the R programming language. Each snippet is framed in a box with rounded corners. ### Code Snippets: 1. **df %>% summarise(mean = mean(magnitude), sd = sd(magnitude))** - Explanation: This code uses the `summarise()` function from the `dplyr` package to calculate the mean and standard deviation (`sd`) of the `magnitude` column in the dataframe `df`. 2. **mean(df$magnitude)** - Explanation: This code calculates the mean of the `magnitude` column in the dataframe `df` using the base R function `mean()`. 3. **sd(df$magnitude)** - Explanation: This code calculates the standard deviation of the `magnitude` column in the dataframe `df` using the base R function `sd()`. 4. **df %>% descriptive(magnitude)** - Explanation: This code appears to be an attempt to use the `descriptive()` function (potentially from a specific package) on the `magnitude` column in the dataframe `df`. However, this function is not a standard function in base R or commonly used packages, suggesting this may be pseudo-code or illustrative. 5. **descriptive(df$magnitude)** - Explanation: Similar to the previous snippet, this code also attempts to use the `descriptive()` function directly on the `magnitude` column of the dataframe `df`. This function name suggests it would provide general descriptive statistics, but it is not standard in base R. 6. **df %>% summarise(mean = magnitude, sd = magnitude)** - Explanation: This code is incorrect as `mean = magnitude` and `sd = magnitude` imply the `magnitude` is already summarized, which doesn't perform any statistical calculation. It should involve functions like `mean()` and `sd()` instead. ### Notes: - The `%>%` operator is known as the pipe operator in the `dplyr` package of R, used to chain operations. - The data frame `df` is used consistently in all snippets for demonstration purposes. - Only the first, second, and third snippets are syntactically correct and meaningful in R for calculating descriptive statistics.
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