Last updated: 2020-08-14

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Rmd 6c088b5 sciencificity 2020-08-14 Add Chapter 1

Do cars with big engines use more fuel than cars with small engines?

Hypothesis: Cars with bigger engines use more fuel, i.e. the fuel efficiency declines as the engine size gets bigger. If miles per gallon was on the y-axis and engine size on the x-axis we would see a decreasing trend.

# A tibble: 234 x 11
   manufacturer model    displ  year   cyl trans   drv     cty   hwy fl    class
   <chr>        <chr>    <dbl> <int> <int> <chr>   <chr> <int> <int> <chr> <chr>
 1 audi         a4         1.8  1999     4 auto(l~ f        18    29 p     comp~
 2 audi         a4         1.8  1999     4 manual~ f        21    29 p     comp~
 3 audi         a4         2    2008     4 manual~ f        20    31 p     comp~
 4 audi         a4         2    2008     4 auto(a~ f        21    30 p     comp~
 5 audi         a4         2.8  1999     6 auto(l~ f        16    26 p     comp~
 6 audi         a4         2.8  1999     6 manual~ f        18    26 p     comp~
 7 audi         a4         3.1  2008     6 auto(a~ f        18    27 p     comp~
 8 audi         a4 quat~   1.8  1999     4 manual~ 4        18    26 p     comp~
 9 audi         a4 quat~   1.8  1999     4 auto(l~ 4        16    25 p     comp~
10 audi         a4 quat~   2    2008     4 manual~ 4        20    28 p     comp~
# ... with 224 more rows
# create coordinate system
ggplot(data = mpg, aes(x = displ,
                       y = hwy))

ggplot(data = mpg) +
  geom_point(mapping = aes(x = displ,
                           y = hwy))

My hypothesis has been confirmed.

num_rows <- nrow(mtcars)
num_cols <- ncol(mtcars)
ex4_plot <- ggplot(data = mpg,
                   aes(x = hwy,
                       y = cyl)) +


  1. Run ggplot(data = mpg). What do you see?
    Ans: An empty canvas of a plot. If you add the aes(x = xx, y = yy) you will see an empty canvas with the axes drawn.
  2. How many rows are there in mtcars? Columns?
    Ans: Number of rows is 32, cols is 11.
  3. What does the drv variable describe? Ans: ‘The type of drive train, where f = front-wheel drive, r = rear wheel drive, 4 = 4wd’
  4. Make a scatterplot of hwy versus cyl.

  1. What happens if you make a scatterplot of class versus drv? Why is this plot not useful?
ggplot(data = mpg, aes(x = class, 
                       y = drv)) +

These are 2 categorical variables here so this isn’t very useful.

R version 3.6.3 (2020-02-29)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)

Matrix products: default

[1] LC_COLLATE=English_South Africa.1252  LC_CTYPE=English_South Africa.1252   
[3] LC_MONETARY=English_South Africa.1252 LC_NUMERIC=C                         
[5] LC_TIME=English_South Africa.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] forcats_0.5.0   stringr_1.4.0   dplyr_1.0.0     purrr_0.3.4    
 [5] readr_1.3.1     tidyr_1.1.0     tibble_3.0.3    ggplot2_3.3.0  
 [9] tidyverse_1.3.0 workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] tidyselect_1.1.0 xfun_0.13        haven_2.2.0      lattice_0.20-38 
 [5] colorspace_1.4-1 vctrs_0.3.2      generics_0.0.2   htmltools_0.4.0 
 [9] yaml_2.2.1       utf8_1.1.4       rlang_0.4.7      later_1.0.0     
[13] pillar_1.4.6     withr_2.2.0      glue_1.4.1       DBI_1.1.0       
[17] dbplyr_1.4.3     modelr_0.1.6     readxl_1.3.1     lifecycle_0.2.0 
[21] munsell_0.5.0    gtable_0.3.0     cellranger_1.1.0 rvest_0.3.5     
[25] evaluate_0.14    labeling_0.3     knitr_1.28       httpuv_1.5.2    
[29] fansi_0.4.1      broom_0.5.6      Rcpp_1.0.4.6     promises_1.1.0  
[33] backports_1.1.6  scales_1.1.0     jsonlite_1.7.0   farver_2.0.3    
[37] fs_1.4.1         hms_0.5.3        digest_0.6.25    stringi_1.4.6   
[41] grid_3.6.3       rprojroot_1.3-2  cli_2.0.2        tools_3.6.3     
[45] magrittr_1.5     crayon_1.3.4     whisker_0.4      pkgconfig_2.0.3 
[49] ellipsis_0.3.1   xml2_1.3.2       reprex_0.3.0     lubridate_1.7.8 
[53] rstudioapi_0.11  assertthat_0.2.1 rmarkdown_2.1    httr_1.4.2      
[57] R6_2.4.1         nlme_3.1-144     git2r_0.26.1     compiler_3.6.3