Here’s what we want to accomplish in this class:

  1. Finish discussion of data wrangling/factors [slides]. 1, Discuss the intuition and formulas for avg and SD.
  2. group_by()/summarize() [slides].
  3. Discuss normal approximation [slides]
  4. Discuss homework.
# load packages
library(tidyverse)
library(kableExtra)

# load an example dataset
data(gapminder, package = "gapminder")

# quick look at the example dataset
glimpse(gapminder)
## Rows: 1,704
## Columns: 6
## $ country   <fct> "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", …
## $ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
## $ year      <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, …
## $ lifeExp   <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854, 40.8…
## $ pop       <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880372, 12…
## $ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.1134, …
# find the average lifeExp for each continent in 2007
smry <- gapminder %>%
  filter(year == 2007) %>%
  group_by(continent) %>%
  summarize(avg_life_exp = mean(lifeExp)) %>%
  glimpse()
## Rows: 5
## Columns: 2
## $ continent    <fct> Africa, Americas, Asia, Europe, Oceania
## $ avg_life_exp <dbl> 54.80604, 73.60812, 70.72848, 77.64860, 80.71950
# make a table
smry %>%
  mutate(avg_life_exp = round(avg_life_exp)) %>%
  rename(Continent = continent, `Average Life Expectancy` = avg_life_exp) %>%
  kable()
Continent Average Life Expectancy
Africa 55
Americas 74
Asia 71
Europe 78
Oceania 81 
# find the average lifeExp for each continent and year
smry <- gapminder %>%
  group_by(continent, year) %>%
  summarize(avg_life_exp = mean(lifeExp)) %>%
  glimpse()
## `summarise()` has grouped output by 'continent'. You can override using the
## `.groups` argument.
## Rows: 60
## Columns: 3
## Groups: continent [5]
## $ continent    <fct> Africa, Africa, Africa, Africa, Africa, Africa, Africa, A…
## $ year         <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 199…
## $ avg_life_exp <dbl> 39.13550, 41.26635, 43.31944, 45.33454, 47.45094, 49.5804…
# make a table
smry %>%
  mutate(avg_life_exp = round(avg_life_exp)) %>%
  pivot_wider(names_from = year, values_from = avg_life_exp) %>%
    rename(Continent = continent) %>%
  kable()
Continent 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007
Africa 39 41 43 45 47 50 52 53 54 54 53 55
Americas 53 56 58 60 62 64 66 68 70 71 72 74
Asia 46 49 52 55 57 60 63 65 67 68 69 71
Europe 64 67 69 70 71 72 73 74 74 76 77 78
Oceania 69 70 71 71 72 73 74 75 77 78 80 81
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Carlisle Rainey