R Dataset / Package psych / iqitems

How To Create a Barplot

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

How To Create a Stacked Barplot

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

How To Create a Pie Chart

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

How To Compute the Mean

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

How To Create a Plot

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

How to Compute the Median

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

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Correlation Coefficient

Submitted by pmagunia on April 22, 2018 - 3:08 PM
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

Submitted by pmagunia on April 22, 2018 - 3:09 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Dotplot

Submitted by pmagunia on April 22, 2018 - 3:10 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Hollow Histogram

Submitted by pmagunia on April 22, 2018 - 3:10 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Numerical Summaries

Submitted by pmagunia on April 22, 2018 - 2:51 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Pie Chart

Submitted by pmagunia on April 22, 2018 - 3:11 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Plot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Regression

Submitted by pmagunia on April 22, 2018 - 3:12 PM

Stem and Leaf Plots

Submitted by pmagunia on April 22, 2018 - 3:12 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Submitted by pmagunia on March 9, 2018 - 1:06 PM
<iframe src="https://embed.picostat.com/r-dataset-package-psych-iqitems.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-61777.csv 47.86 KB
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 iqitems data set which pertains to 16 multiple choice IQ items. The iqitems data set is found in the psych R package. You can load the iqitems data set in R by issuing the following command at the console data("iqitems"). This will load the data into a variable called iqitems. If R says the iqitems data set is not found, you can try installing the package by issuing this command install.packages("psych") 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 iqitems R data set. The size of this file is about 49,011 bytes.


16 multiple choice IQ items

Description

16 multiple choice ability items taken from the Synthetic Aperture Personality Assessment (SAPA) web based personality assessment project. The data from 1525 subjects are included here as a demonstration set for scoring multiple choice inventories and doing basic item statistics. For more information on the development of an open source measure of cognitive ability, consult the readings available at the personality-project.org.

Usage

data(iqitems)

Format

A data frame with 1525 observations on the following 16 variables. The number following the name is the item number from SAPA.

reason.4

Basic reasoning questions

reason.16

Basic reasoning question

reason.17

Basic reasoning question

reason.19

Basic reasoning question

letter.7

In the following alphanumeric series, what letter comes next?

letter.33

In the following alphanumeric series, what letter comes next?

letter.34

In the following alphanumeric series, what letter comes next

letter.58

In the following alphanumeric series, what letter comes next?

matrix.45

A matrix reasoning task

matrix.46

A matrix reasoning task

matrix.47

A matrix reasoning task

matrix.55

A matrix reasoning task

rotate.3

Spatial Rotation of type 1.2

rotate.4

Spatial Rotation of type 1.2

rotate.6

Spatial Rotation of type 1.1

rotate.8

Spatial Rotation of type 2.3

Details

16 items were sampled from 80 items given as part of the SAPA (http://sapa-project.org) project (Revelle, Wilt and Rosenthal, 2009; Condon and Revelle, 2014) to develop online measures of ability. These 16 items reflect four lower order factors (verbal reasoning, letter series, matrix reasoning, and spatial rotations. These lower level factors all share a higher level factor ('g').

This data set and the associated data set (ability based upon scoring these multiple choice items and converting them to correct/incorrect may be used to demonstrate item response functions, tetrachoric correlations, or irt.fa as well as omega estimates of of reliability and hierarchical structure.

In addition, the data set is a good example of doing item analysis to examine the empirical response probabilities of each item alternative as a function of the underlying latent trait. When doing this, it appears that two of the matrix reasoning problems do not have monotonically increasing trace lines for the probability correct. At moderately high ability (theta = 1) there is a decrease in the probability correct from theta = 0 and theta = 2.

Source

The example data set is taken from the Synthetic Aperture Personality Assessment personality and ability test at http://sapa-project.org. The data were collected with David Condon from 8/08/12 to 8/31/12.

References

Revelle, William, Wilt, Joshua, and Rosenthal, Allen (2010) Personality and Cognition: The Personality-Cognition Link. In Gruszka, Alexandra and Matthews, Gerald and Szymura, Blazej (Eds.) Handbook of Individual Differences in Cognition: Attention, Memory and Executive Control, Springer.

Condon, David and Revelle, William, (2014) The International Cognitive Ability Resource: Development and initial validation of a public-domain measure. Intelligence, 43, 52-64.

Examples

## Not run: 
data(iqitems)
iq.keys <- c(4,4,4, 6,  6,3,4,4,   5,2,2,4,   3,2,6,7)
score.multiple.choice(iq.keys,iqitems)   #this just gives summary statisics
#convert them to true false 
iq.scrub <- scrub(iqitems,isvalue=0)  #first get rid of the zero responses
iq.tf <-  score.multiple.choice(iq.keys,iq.scrub,score=FALSE) 
              #convert to wrong (0) and correct (1) for analysis
describe(iq.tf) 
#see the ability data set for these analyses
#now, for some item analysis
#iq.irt <- irt.fa(iq.tf)  #do a basic irt
#iq.sc <-score.irt(iq.irt,iq.tf)  #find the scores
#op <- par(mfrow=c(4,4))
#irt.responses(iq.sc[,1], iq.tf)  
#op <- par(mfrow=c(1,1))## End(Not run)

--

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
R Dataset / Package vcd / JointSports March 9, 2018 - 1:06 PM Dataset
R Dataset / Package mosaicData / Riders March 9, 2018 - 1:06 PM Dataset
R Dataset / Package MASS / epil March 9, 2018 - 1:06 PM Dataset
R Dataset / Package HSAUR / schizophrenia2 March 9, 2018 - 1:06 PM Dataset
stent365 May 7, 2017 - 12:27 AM Dataset