My Blog: Bootstrapping

Load the R packages we will use.

library(tidyverse)
library(moderndive)
library(infer)
library(fivethirtyeight)

what is the average age of members that have served in Congress? - set random seed generator to 123 - take a sample of 100 from the dataset congress_age and assign it to congress_age_100

set.seed(123)
congress_age_100 <- congress_age  %>% 
  rep_sample_n(size = 100)

congress_age is the population and congress_age_100 is the sample
100 is the number of observations in the population and 123 is the number of observations in your sample

Construct the confidence interval

1. Use specify to indicate the variable from congress_age_100 that you are interested in

congress_age_100  %>% 
  specify(response = age)

Response: age (numeric)
# A tibble: 100 x 1
     age
   <dbl>
 1  53.1
 2  54.9
 3  65.3
 4  60.1
 5  43.8
 6  57.9
 7  55.3
 8  46  
 9  42.1
10  37  
# ... with 90 more rows

2. generate 1000 replicates of your sample of 100

congress_age_100  %>% 
  specify(response = age)  %>% 
  generate(reps = 1000, type = "bootstrap")

Response: age (numeric)
# A tibble: 100,000 x 2
# Groups:   replicate [1,000]
   replicate   age
       <int> <dbl>
 1         1  42.1
 2         1  71.2
 3         1  45.6
 4         1  39.6
 5         1  56.8
 6         1  71.6
 7         1  60.5
 8         1  56.4
 9         1  43.3
10         1  53.1
# ... with 99,990 more rows

3. calculate the mean for each replicate

Assign to bootstrap_distribution_mean_age
Display bootstrap_distribution_mean_age

bootstrap_distribution_mean_age  <- congress_age_100  %>% 
  specify(response = age)  %>% 
  generate(reps = 1000, type = "bootstrap")  %>% 
  mean(stat = "age")

bootstrap_distribution_mean_age

[1] NA

4. visualize the bootstrap distribution

calculate the 95% confidence interval using the percentile method

Assign the output to congress_ci_percentile
Display congress_ci_percentile

Calculate the observed point estimate of the mean and assign it to obs_mean_age

Display obs_mean_age