Children’s Games

Setting up R Packages

Plot Theme

Show the Code
# https://stackoverflow.com/questions/74491138/ggplot-custom-fonts-not-working-in-quarto

# Chunk options
knitr::opts_chunk$set(
  fig.width = 7,
  fig.asp = 0.618, # Golden Ratio
  # out.width = "80%",
  fig.align = "center"
)
### Ggplot Theme
### https://rpubs.com/mclaire19/ggplot2-custom-themes

theme_custom <- function() {
  font <- "Roboto Condensed" # assign font family up front

  theme_classic(base_size = 14) %+replace% # replace elements we want to change

    theme(
      panel.grid.minor = element_blank(), # strip minor gridlines
      text = element_text(family = font),
      # text elements
      plot.title = element_text( # title
        family = font, # set font family
        size = 16, # set font size
        face = "bold", # bold typeface
        hjust = 0, # left align
        # vjust = 2                #raise slightly
        margin = margin(0, 0, 10, 0)
      ),
      plot.subtitle = element_text( # subtitle
        family = font, # font family
        size = 14, # font size
        hjust = 0,
        margin = margin(2, 0, 5, 0)
      ),
      plot.caption = element_text( # caption
        family = font, # font family
        size = 8, # font size
        hjust = 1
      ), # right align

      axis.title = element_text( # axis titles
        family = font, # font family
        size = 10 # font size
      ),
      axis.text = element_text( # axis text
        family = font, # axis family
        size = 8
      ) # font size
    )
}

# Set graph theme
theme_set(new = theme_custom())
#

Introduction

Children in the ages of 6 to 7 years are asked if they want to play two games. This dataset pertains to their responses about the two games. The research is based on this paper:

Lin Bian et al. ,Gender stereotypes about intellectual ability emerge early and influence children’s interests. Science 355,389-391(2017).DOI:10.1126/science.aah6524. This very short and crisp paper is available here.

Read the Data

The data is part of the R package openintro. Yes, install it. From the help menu ?children_gender_stereo:

This data object is more unusual than most. It is a list of 4 data frames. The four data frames correspond to the data used in Studies 1-4 of the referenced paper, and these data frames each have variables (columns) that are explained below:

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library(openintro)
data("children_gender_stereo")
glimpse(children_gender_stereo)
List of 4
 $ 1:'data.frame':  192 obs. of  5 variables:
  ..$ subject   : int [1:192] 1 2 3 4 5 6 7 8 9 10 ...
  ..$ gender    : chr [1:192] "female" "female" "female" "male" ...
  ..$ age       : int [1:192] 7 7 7 6 7 5 5 5 5 5 ...
  ..$ trait     : chr [1:192] "smart" "smart" "smart" "smart" ...
  ..$ stereotype: num [1:192] 0.611 0.278 0.722 0.556 1 ...
 $ 2:'data.frame':  576 obs. of  7 variables:
  ..$ subject             : int [1:576] 1 2 3 4 5 6 7 8 9 10 ...
  ..$ gender              : chr [1:576] "male" "male" "male" "female" ...
  ..$ age                 : int [1:576] 6 5 7 5 5 7 6 6 5 5 ...
  ..$ trait               : chr [1:576] "smart" "smart" "smart" "smart" ...
  ..$ target              : chr [1:576] "adults" "adults" "adults" "adults" ...
  ..$ stereotype          : num [1:576] 0.75 1 0.25 1 0.25 0.75 0 0.5 0.75 1 ...
  ..$ high_achieve_caution: num [1:576] 0.25 1 0.25 1 0.75 0.5 0.5 0.75 0.5 0.5 ...
 $ 3:'data.frame':  128 obs. of  7 variables:
  ..$ subject   : int [1:128] 1 2 3 4 5 6 7 8 9 10 ...
  ..$ gender    : chr [1:128] "female" "male" "female" "male" ...
  ..$ age       : int [1:128] 7 7 7 7 7 6 7 7 6 6 ...
  ..$ game      : chr [1:128] "smart" "smart" "smart" "smart" ...
  ..$ interest  : num [1:128] 0.328 0.781 0.781 -0.213 -2.304 ...
  ..$ difference: num [1:128] 0.244 0.453 0.209 -0.577 -1.523 ...
  ..$ stereotype: num [1:128] -1.7982 0.0866 -1.7982 0.7784 -0.6051 ...
 $ 4:'data.frame':  96 obs. of  4 variables:
  ..$ subject : int [1:96] 1 2 3 4 5 6 7 8 9 10 ...
  ..$ gender  : chr [1:96] "female" "female" "female" "female" ...
  ..$ age     : int [1:96] 6 6 6 6 6 6 6 6 6 6 ...
  ..$ interest: num [1:96] 0.3924 0.68 -0.7163 -0.4279 -0.0413 ...

Let us choose, arbitrarily, the third study:

## Choosing, arbitrarily, the third game/third study
children_gender_stereo[[3]] -> games3
glimpse(games3)
Rows: 128
Columns: 7
$ subject    <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, …
$ gender     <chr> "female", "male", "female", "male", "female", "female", "ma…
$ age        <int> 7, 7, 7, 7, 7, 6, 7, 7, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 6, 6,…
$ game       <chr> "smart", "smart", "smart", "smart", "smart", "smart", "smar…
$ interest   <dbl> 0.328241235, 0.781351865, 0.781351865, -0.213178560, -2.303…
$ difference <dbl> 0.24441071, 0.45311063, 0.20869992, -0.57713058, -1.5226918…
$ stereotype <dbl> -1.79820307, 0.08662039, -1.79820307, 0.77835148, -0.605110…

Data Dictionary

Quantitative Variables

Write in.

Qualitative Variables

Write in.

Observations

Write in.

Analyse/Transform the Data

```{r}
#| label: data-preprocessing
#
# Write in your code here
# to prepare this data as shown below
# to generate the plot that follows
# Counts, histograms etc
```

Research Question

Note

Is there a difference the average interest level between Boys and Girls for the two kinds of games, “Smart Game” and “Try Hard Game”? Does that lead to the inference of how children acquire gender stereotypes about play?

Plot the Data

Task and Discussion

Complete the Data Dictionary. Select and Transform the variables as shown. Create the graphs shown below and discuss the following questions:

  • Identify the type of charts
  • Identify the variables used for various geometrical aspects (x, y, fill…). Name the variables appropriately.
  • What research activity might have been carried out to obtain the data graphed here? Provide some details.
  • Does the Chart answer the Hypothesis? Justify?
  • Write a 2-line story based on the chart, describing your inference/surprise.
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