This article is part of the R for Researchers series. For a list of topics covered by this series, see the Introduction article. If you're new to R we highly recommend reading the articles in order.

This article has the completed SalDoc.Rmd file. The material explaining the construction of this table are contained in the Data presentation article.

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  • The completed SalDoc.Rmd files should look similar to the following

    ---
    title: "Analysis of Professor Salaries"
    fontsize: 12pt
    geometry: margin=1in
    documentclass: article
    
    output: 
      pdf_document:
        fig_caption: yes
    ---
    
    ```{r, echo=FALSE}
    targetType <- "latex"
    
    #
    # table numbers
    #
    tabNumRankByDscpl <- 1
    
    #
    # figure numbers
    #
    FigNumYrsFacRank <- 1
    FigNumBoxDscplFacRank <- 2
    FigNumGenYrsFacDscpl <- 3
    FigNumBoxGenRankFacDscpl <- 4
    ```
    
    ```{r, echo=FALSE, results="hide", message=FALSE, warning=FALSE, fig.show="hide"}  
    source("SalAnalysis.R")  
    ```
    
    ## Data overview
    
    
    The Salaries data set is the basis for this analysis.
    It is a sample of academic salaries of Professors at
    United States universities from the 2008-9 school year.
    The salary information was collected to monitor the
    difference in salaries between men and women.
    
    ```{r, echo=FALSE, results="hide", message=FALSE, warning=FALSE, fig.show="hide"}  
    vars <- colnames(SalariesIn)  
    dscplNames <- levels(salary$dscpl)
    rankNames <- levels(salary$rank)
    ```
    
    The data set included `r length(salary$salary)` professors.
    The variables included in the data set are 
    `r paste(vars[-length(vars)],collapse=", ")`,
    and `r vars[length(vars)]`. 
    The sampled professors had ranks of
    `r paste(rankNames[-length(rankNames)],collapse=", ")`,
    and `r rankNames[length(rankNames)]`
    and were from disciplines 
    `r paste(dscplNames[-length(dscplNames)],collapse=", ")`
    and `r dscplNames[length(dscplNames)]`.
    The numbers of professors from each of these groups is
    displayed in table `r tabNumRankByDscpl`.
    There are about 20 percent more members of discipline B
    included in the sample than of discipline A.
    The table shows there are a greater proportion of Discipline B 
    members with a rank of associate or assistant professor.
    
    ```{r, echo=FALSE }
    tempTab <- table(salary$rank,salary$dscpl)
    rankByDscpl <- as.data.frame.matrix(tempTab)
    rankByDscpl$Totals <- rowSums(tempTab)
    rankByDscpl["Totals",] <- colSums(rankByDscpl)
    rankByDscpl
    ```
    
    ```{r, echo=FALSE, results="asis"}
    xtab <- xtable(rankByDscpl,
                       caption="Count of Professors by discipline and Rank",
                       display=c("s","d","d","d"),
                       align="|r|rr|r|"
                       )
    print(xtab, 
          type=targetType, 
          caption.placement="top", 
          hline.after=c(-1,0,3,4),
          comment=FALSE
          )
    ```
    
    The relationship between years of service and salary can be
    seen in figure `r FigNumYrsFacRank`.
    The panels seem to indicate that for associate and assistant 
    professors most of the members of discipline B have higher 
    salaries than most of the members of discipline A, at the
    same rank.
    The box plots, figure `r FigNumBoxDscplFacRank`, also supports 
    this observation.
    
    ```{r, echo=FALSE, fig.cap="Salaries  by discipline and rank", fig.height=2.75, fig.width=5.5 } 
    plotYrsFacRank
    ```
    
    ```{r, echo=FALSE, fig.cap="Salaries summarized by discipline and rank", fig.height=2.75, fig.width=5.5 } 
    boxDscplFacRank
    ```        
    
    The plots of salaries with color indicators for gender, figure
    `r FigNumGenYrsFacDscpl`, indicates there may be a gender
    difference in salary in discipline A.
    The box plots in figure `r FigNumBoxGenRankFacDscpl`
    indicate that the difference between the genders in
    discipline A is greatest at the rank of assistant professor.
    
    The plots of salaries with color indicators for gender, figure
    `r FigNumGenYrsFacDscpl`, indicates there may be a gender
    difference in salary in discipline A.
    The box plots in figure `r FigNumBoxGenRankFacDscpl` indicate
    that the difference between the genders in discipline A is 
    greatest at the rank of assistant professor.
    
    ```{r, echo=FALSE, fig.cap="Salaries by gender and discipline", fig.height=2.75, fig.width=5.5 } 
    plotYrsFacDscpl
    ```
    
    ```{r, echo=FALSE, fig.cap="Salaries summarized by gender and discipline", fig.height=3, fig.width=5.5 } 
    boxGenRankFacDscpl
    ```

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Last Revised: 2/16/2015