littleSurvey: Results from a little survey

In fastR: Data sets and utilities for Foundations and Applications of Statistics by R Pruim

Description

These data are from a little survey given to a number of students in introductory statistics courses. Several of the items were prepared in multiple versions and distributed randomly to the students.

Usage

data(littleSurvey)

Format

A data frame with 279 observations on the following 20 variables.

number

a number between 1 and 30

colorVer

which version of the 'favorite color' question was on the survey. A factor with levels v1 v2

color

favorite color if among predefined choices. A factor with levels black green other purple red

otherColor

favorite color if not among choices above.

animalVer

which version of the 'favorite color' question was on the survey. A factor with levels v1 v2

animal

favorite animal if among predefined choices. A factor with levels elephant giraffe lion other.

otherAnimal

favorite animal if not among the predefined choices.

pulseVer

which version of the 'pulse' question was on the survey

pulse

self-reported pulse

TVver

which of three versions of the TV question was on the survey

tvBox

a factor with levels <1 >4 >8 1-2 2-4 4-8 none other

tvHours

a numeric vector

surpriseVer

which of two versions of the 'surprise' question was on the survey

surprise

a factor with levels no yes

playVer

which of two versions of the 'play' question was on the survey

play

a factor with levels no yes

diseaseVer

which of two versions of the 'play' question was on the survey

disease

a factor with levels A B

homeworkVer

which of two versions of the 'homework' question was on the survey

homework

a factor with levels A B

Examples

data(littleSurvey)
xtabs(~surprise+surpriseVer,littleSurvey)
xtabs(~disease+diseaseVer,littleSurvey)

Example output

Loading required package: mosaic
Loading required package: dplyr

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Loading required package: lattice
Loading required package: ggformula
Loading required package: ggplot2
Loading required package: ggstance

Attaching package: 'ggstance'

The following objects are masked from 'package:ggplot2':

    GeomErrorbarh, geom_errorbarh


New to ggformula?  Try the tutorials: 
	learnr::run_tutorial("introduction", package = "ggformula")
	learnr::run_tutorial("refining", package = "ggformula")
Loading required package: mosaicData
Loading required package: Matrix

The 'mosaic' package masks several functions from core packages in order to add 
additional features.  The original behavior of these functions should not be affected by this.

Note: If you use the Matrix package, be sure to load it BEFORE loading mosaic.

Attaching package: 'mosaic'

The following object is masked from 'package:Matrix':

    mean

The following object is masked from 'package:ggplot2':

    stat

The following objects are masked from 'package:dplyr':

    count, do, tally

The following objects are masked from 'package:stats':

    IQR, binom.test, cor, cor.test, cov, fivenum, median, prop.test,
    quantile, sd, t.test, var

The following objects are masked from 'package:base':

    max, mean, min, prod, range, sample, sum

Loading required package: mosaicCalc
Loading required package: mosaicCore

Attaching package: 'mosaicCore'

The following objects are masked from 'package:dplyr':

    count, tally


Attaching package: 'mosaicCalc'

The following object is masked from 'package:stats':

    D


Attaching package: 'fastR'

The following object is masked from 'package:graphics':

    panel.smooth

        surpriseVer
surprise  v1  v2
     no  118  99
     yes  24  37
       diseaseVer
disease v1 v2
      A 71 53
      B 73 81

fastR documentation built on May 2, 2019, 5:53 p.m.