R Dataset / Package Ecdat / UStaxWords

How To Create a Barplot

Webform
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

How To Create a Stacked Barplot

Webform
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

How To Create a Pie Chart

Webform
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

How To Compute the Mean

Webform
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

How To Create a Plot

Webform
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

How to Compute the Median

Webform
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Boxplot

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Correlation Coefficient

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Cumulative Frequency Histogram

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Dotplot

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Hollow Histogram

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Numerical Summaries

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Pie Chart

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Plot

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Regression

Stem and Leaf Plots

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Visual Summaries

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Embed
<iframe src="https://embed.picostat.com/r-dataset-package-ecdat-ustaxwords.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-29387.csv 503 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the UStaxWords data set which pertains to Number of Words in US Tax Law. The UStaxWords data set is found in the Ecdat R package. You can load the UStaxWords data set in R by issuing the following command at the console data("UStaxWords"). This will load the data into a variable called UStaxWords. If R says the UStaxWords data set is not found, you can try installing the package by issuing this command install.packages("Ecdat") 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 UStaxWords R data set. The size of this file is about 503 bytes.


Number of Words in US Tax Law

Description

Thousands of words in US tax law for 1995 to 2015 in 10 year intervals. This includes income taxes and all taxes in the code itself (written by congress) and regulations (written by government administrators). For 2015 only "EntireTaxCodeAndRegs" is given; for other years, this number is broken down by income tax vs. other taxes and code vs. regulations.

Usage

data(UStaxWords)

Format

A data.frame containing:

year

tax year

IncomeTaxCode

number of words in thousands in the US income tax code

otherTaxCode

number of words in thousands in US tax code other than income tax

EntireTaxCode

number of words in thousands in the US tax code

IncomeTaxRegulations

number of words in thousands in US income tax regulations

otherTaxRegulations

number of words in thousands in US tax regulations other than income tax

IncomeTaxCodeAndRegs

number of words in thousands in both the code and regulations for the US income tax

otherTaxCodeAndRegs

number of wrds in thousands in both code and regulations for US taxes apart from income taxes.

EntireTaxCodeAndRegs

number of words in thousands in US tax code and regulations

Details

Thousands of words in the US tax code and federal tax regulations, 1955-2015. This is based on data from the Tax Foundation (taxfoundation.org), adjusted to eliminate an obvious questionable observation in otherTaxRegulations for 1965. The numbers of words in otherTaxRegulations was not reported directly by the Tax Foundation but is easily computed as the difference between their Income and Entire tax numbers. This series shows the numbers falling by 48 percent between 1965 and 1975 and by 1.5 percent between 1995 and 2005. These are the only declines seen in these numbers and seem inconsistent with the common concern (expressed e.g., in Moody, Warcholik and Hodge, 2005) about the difficulties of simplifying any governmental program, because vested interest appear to defend almost anything. Lessig (2011) notes that virtually all provisions of US law that favor certain segments of society are set to expire after a modest number of years. These sunset provisions provide recurring opportunities for incumbent politicians to extort campaign contributions from those same segments to ensure the continuation of the favorable treatment.

The decline of 48 percent in otherTaxRegulations seems more curious for two additional reasons: First, it was preceded by a tripling of otherTaxRegulations between 1955 and 1965. Second, it was NOT accompanied by any comparable behavior of otherTaxCode. Instead, the latter grew each decade by between 17 and 53 percent, similar to but slower than the growth in IncomeTaxCode and IncomeTaxRegulations.

Accordingly, otherTaxRegulations for 1965 is replaced by the average of the numbers for 1955 and 1975, and EntireTaxRegulations for 1965 is comparably adjusted. This replaces (1322, 2960) for those two variables for 1965 with (565, 2203). In addition, otherTaxCodeAndRegs and EntireTaxCodeAndRegulations are also changed from (1626, 3507) to (870, 2751).

Independent of whether this adjustment is correct or not, it's clear that there have been roughly 3 words of regulations for each word in the tax code. Most of these are income tax regulations, which have recently contained 4.5 words for every word in code. The income tax code currently includes roughly 50 percent more words than other tax code.

Author(s)

Spencer Graves

Source

Tax Foundation: Number of Words in Internal Revenue Code and Federal Tax Regulations, 1955-2005 Scott Greenberg, "Federal Tax Laws and Regulations are Now Over 10 Million Words Long", October 08, 2015

References

J. Scott Moody, Wendy P. Warcholik, and Scott A. Hodge (2005) "The Rising Cost of Complying with the Federal Income Tax", The Tax Foundation Special Report No. 138.

Examples

data(UStaxWords)
plot(EntireTaxCodeAndRegs/1000 ~ year, UStaxWords, 
  type='b',
  ylab='Millions of words in US tax code & regs')# Write to a file for Wikimedia Commons
## Not run: 
svg('UStaxWords.svg')## End(Not run)
matplot(UStaxWords$year, UStaxWords[c(2:3, 5:6)]/1000,
    type='b', bty='n', ylab='',
    ylim=c(0, max(UStaxWords$EntireTaxCodeAndRegs)/1000),
    las=1, xlab="", cex.axis=2)
lines(EntireTaxCodeAndRegs/1000~year, UStaxWords, lwd=2)
## Not run: 
dev.off()## End(Not run)
# lines 1:4 = IncomeTaxCode, otherTaxCode, 
#   IncomeTaxRegulations,
#   and otherTaxRegulations, respectively##
## Plotting the original numbers without the adjustment
##
UStax. <- UStaxWords
UStax.[2,c(6:7, 9:10)] <- c(1322, 2960, 1626, 3507)
matplot(UStax.$year, UStax.[c(2:3, 5:6)]/1000,
      type='b', bty='n', ylab='',
      ylim=c(0, max(UStax.$EntireTaxCodeAndRegs)/1000),
      las=1, xlab="", cex.axis=2)
lines(EntireTaxCodeAndRegs/1000~year, UStax., lwd=2)
# Note especially the anomalous behaviour of line 4 =
# otherTaxRegulations.  As noted with "details" above,
# otherTaxRegulations could have tripled between 1955 
# and 1965, then fallen by 48 percent between 1965 and
# 1975.  However, that does not seem credible, 
# especially since there was no corresponding behavior 
# in otherTaxCode.##
## linear trend 
##
(newWdsPerYr <- lm(EntireTaxCodeAndRegs~year, 
    UStaxWords))
plot(UStaxWords$year, resid(newWdsPerYr))
# Roughly 150,000 additional words added each year
# since 1955.  
# No indication of nonlinearity.  
--

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

Picostat Manual
How To Register With a Username
  1. Go to the user registration page.
  2. Enter a username and email address into the form.
  3. Answer the ReCaptcha (this is used to prevent spam).
  4. Click Submit.
  5. Click the link that was sent to the email address you registered with.
  6. Clicking the link will open another page on Picostat where you can select a password.
  7. Click Save and enter any profile details you wish to enter.
How To Register With Google Single Sign On (SSO)
  1. Go to the user login page.
  2. Click the Google button that says "Sign in with Google". This will redirect you to a page controlled by Google.
  3. Enter your Google username and password if you are not already authenticated.
  4. Review the Picostat Terms of Use and Privacy Policy. Then submit the Google form if you accept the terms.
  5. Google will redirect you back to Picostat with your new account created and you will be logged in.
  6. Enter any profile details you wish to share.
How To Login With a Username and Password
  1. Go to the user login page.
  2. Enter your username and password that you registered with.
  3. Click "Login". You will be redirected to your user homepage authenticated.
How To Login With Google Single Sign On (SSO)
  1. Go to the user login page.
  2. Click the button that says "Sign in with Google".
  3. If you already registered with Picostat via Google SSO, you will be redirected to your user homepage authenticated.
How To Import a Dataset
  1. Create a Picostat account or login with your existing picostat account (see above).
  2. Go to the dataset import page.
  3. Select a license for the dataset. The default is "No License" but allows Picostat to host a copy of the dataset as per the privacy policy. You may wish to uncheck the "Public" option if you do not wish to share your dataset with others. R Datasets that come by downloading R have a GNU General Public License v3.0 which may also be selected from the Picostat dropdown.
  4. Enter a title for the dataset
  5. Choose a dataset input methods. Available options include:
    • Random data - this populates your dataset with random numbers between 0 and 100. You can specify the number of rows and columns for the random dataset.
    • CSV, TSV or TXT file - you will have the option upload a file within the current file size limit and also specify the header and whether or not the dataset is a contingency table. With contingency tables, the first column becomes a label for the rows. Currently with Picostat, there is limited support for contingency tables. Choose "Yes" to the Header option if the first line of the data contains titles for the rows. Also choose the Separator for the dataset. A separator is what breaks the data up. In some cases, a comma would separate data values in a row. You will also have the option to add documentation in the form keyboarded text and also uploaded documentation attachments. You can also specify a license for the documentation.
    • Copy and Paste. This selection contains many of the same fields as importing a file with an additional textarea to copy and paste data to.
    • Empty dataset. Start with a blank dataset and manually add data with the Picostat dataset editor.
    • Excel file - Choose this option if you would like to convert your Excel spreadsheet to a Picostat dataset. With this selection, you will have the option to specify whether to use the first row in the Excel file as column names. If you would like to choose a specific sheet to use, you can also specify with entering its name in the text input.
    • sas7bdat file - SAS is a powerful statistical software package that has its own proprietary file format. Choose this option if you are importing a SAS file.
    • SPSS sav file - SPSS is a statistical package owned by IBM. You can import SPSS files by choosing this option.
  6. Choose whether or not the dataset contains a header. Some of the dataset input methods allow you to specify whether or not a Header exists on the file. Sometimes dataset files contain a Header as the first row which names the columns. If you choose "Yes" to this, the first row in the dataset will become column headers.
  7. You can also add documentation and specify a documentation license. This can be used to help explain your dataset to those unfamiliar with it.
  8. Choose whether or not to upload an supporting attachments.
  9. Pass the captcha. To prevent spam submissions, Picostat has a captcha which is used to prevent automated submissions by bots.
  10. Choose a privacy setting for the dataset. You can also specify whether or not the dataset is Public. If you uncheck this setting, only you and the Picostat administrator will be able to view the dataset.
  11. Submit the form. Once the form is validated, you will be redirected to the dataset homepage where you can choose to edit or perform statistical operations on the dataset.
How To Perform Statistical Analysis with Picostat
  1. Go to any dataset homepage. You can get a full list at the dashboard.
  2. Near the top of the page there will be two drop downs. One for analysis and one for education. Here we will choose Analyis. Choose from one of the following:
    • Numerical Summaries - Here you can get the:
      1. Arithmetic mean
      2. Median
      3. Quartiles
      4. Minimum and Maximum
      5. Stem-and-leaf plot
      6. Standard deviation and Variance
      7. IQR
      8. Cumulative frequencies
    • Plot - a plot of two columns on the cartesian coordinate system
    • Boxplot - a Boxplot (box-and-whisker plot) of a column.
    • Correlation Coefficient - Compute the correlation coefficient between two columns.
    • Cumulative Frequency Histogram - Display a cumulative frequency histogram
    • Dotplot
    • Hollow Histogram - Plot two columns on the same histogram with a different color for each column.
    • Pie Chart
    • Regression - Perform a simple linear regression and compute the p-value and regression line. Also plots the data with the regression line.
    • Stem and Leaf Plots - Plot a one or two-sided stem-and-leaf plot from one or two columns respectively.
    • Visual Summaries - plots the following:
      1. Frequency Histogram
      2. Relative Frequency Histogram
      3. Cumulative Frequency Histogram
      4. Boxplot (Box-and-whisker plot)
      5. Dotplot
  3. PDF - Check this box if you want to download a PDF of the output from the statistical analysis application.
  4. HTML - Check this box if you want a link to the HTML page created with the application.
  5. R File - Check this box if you want a link to download the R commands used to generate output from this statistical application. You should be able to copy the commands verbatim into R Studio or R to recreate the analysis.
How To Use Educational Applications with Picostat
  1. Go to any dataset homepage. You can get a full list at the dashboard.
  2. Near the top of the page there will be two drop downs. One for analysis and one for education. Here we will choose Education. Choose from one of the following:
    • How To Create a Barplot - This will show you how to create a bar chart after selecting a column with the mouse.
    • How To Create a Stacked Barplot - This application will show you how to create a stacked bar plot from a column vector.
    • How To Create a Pie Chart - This application will show you how to create a pie chart from a column of data
    • How To Compute the Mean - This application will show you how to compute the mean from a column vector
    • How To Create a Plot - This app will show you how to plot two columns in the cartesian coordinate system.
    • How To Compute the Media - This statisistical app will show you how to compute the median from a column vector.
  3. PDF - Check this box if you want to download a PDF of the output from the education application.
  4. HTML - Check this box if you want a link to the HTML page created with the application.
Recent Queries For This Dataset

No queries made on this dataset yet.

Title Authored on Content type
OpenIntro Statistics Dataset - gpa_study_hours August 9, 2020 - 12:25 PM Dataset
R Dataset / Package MASS / petrol March 9, 2018 - 1:06 PM Dataset
R Dataset / Package HistData / Snow.streets March 9, 2018 - 1:06 PM Dataset
R Dataset / Package datasets / WWWusage March 9, 2018 - 1:06 PM Dataset
R Dataset / Package DAAG / dewpoint March 9, 2018 - 1:06 PM Dataset