R Dataset / Package Stat2Data / Clothing

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Regression

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<iframe src="https://embed.picostat.com/r-dataset-package-stat2data-clothing.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-26448.csv 1.37 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the Clothing data set which pertains to Clothing. The Clothing data set is found in the Stat2Data R package. You can load the Clothing data set in R by issuing the following command at the console data("Clothing"). This will load the data into a variable called Clothing. If R says the Clothing data set is not found, you can try installing the package by issuing this command install.packages("Stat2Data") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Clothing R data set. The size of this file is about 1,407 bytes.

Documentation

Clothing

Description

Clothing retailer

Format

A dataset with 60 observations on the following 8 variables.

ID Case ID
Amount Net dollar amount spent by customers in their latest purchase from this retailer
Recency Number of months since the last purchase
Freq12 Number of purchases in the last 12 months
Dollar12 Dollar amount of purchases in the last 12 months
Freq24 Number of purchases in the last 24 months
Dollar24 Dollar amount of purchases in the last 24 months
Card 1 for customers who have a private-label credit card with the retailer, 0 if not

Details

This dataset represents a random sample of 60 customers from a large clothing retailer. The manager of the store is interested in predicting how much a customer will spend on his or her next purchase based on one or more of the available explanatory variables.

Source

Personal communication from clothing retailer David Cameron

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Dataset imported from https://www.r-project.org.

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