TV: TV Viewing Data

Description

This data set TV comprises a 5 x 11 x 3 contingency table based on audience viewing data from Neilsen Media Research for the week starting November 6, 1995.

Usage

data(TV)

Arguments

Format

A 5 x 11 x 3 array of cell frequencies with the following structure:


 int [1:5, 1:11, 1:3] 146 244 233 174 294 151 181 161 183 281 ...
 - attr(*, "dimnames")=List of 3
  ..$ Day    : chr [1:5] "Monday" "Tuesday" "Wednesday" "Thursday" ...
  ..$ Time   : chr [1:11] "8:00" "8:15" "8:30" "8:45" ...
  ..$ Network: chr [1:3] "ABC" "CBS" "NBC"

Details

The original data, tv.dat, contains two additional networks: "Fox" and "Other", with small frequencies. These levels were removed in the current version. There is also a fourth factor, transition State transition (turn the television Off, Switch channels, or Persist in viewing the current channel). The TV data here includes only the Persist observations.

References

Friendly, M. and Meyer, D. (2016). Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Boca Raton, FL: Chapman & Hall/CRC. http://ddar.datavis.ca.

Emerson, John W. Mosaic Displays in S-PLUS: A General Implementation and a Case Study. Statistical Graphics and Computing Newsletter, 1998, 9(1), 17--23, http://www.stat.yale.edu/~jay/R/mosaic/v91.pdf

Hartigan, J. A. & Kleiner, B. A Mosaic of Television Ratings. The American Statistician, 1984, 38, 32-35.

Examples

Run this code

data(TV)
structable(TV)
doubledecker(TV)

# reduce number of levels of Time
TV.df <- as.data.frame.table(TV)
levels(TV.df$Time) <- rep(c("8:00-8:59", "9:00-9:59", "10:00-10:44"), 
                          c(4, 4, 3))

TV2 <- xtabs(Freq ~ Day + Time + Network, TV.df)

# re-label for mosaic display
levels(TV.df$Time) <- c("8", "9", "10")
# fit mode of joint independence, showing association of Network with Day*Time
mosaic(~ Day + Network + Time, 
  data = TV.df, 
  expected = ~ Day:Time + Network, 
  legend = FALSE)


# with doubledecker arrangement
mosaic(~ Day + Network + Time, 
  data = TV.df, 
  expected = ~ Day:Time + Network,
  split = c(TRUE, TRUE, FALSE), 
  spacing = spacing_highlighting, 
  legend = FALSE)

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