EXERCISES NUMBER 7

library(openintro)

Loading required package: airports

Loading required package: cherryblossom

Loading required package: usdata

yrbss

# A tibble: 13,583 × 13
     age gender grade hispanic race        height weight helme…¹ text_…² physi…³
   <int> <chr>  <chr> <chr>    <chr>        <dbl>  <dbl> <chr>   <chr>     <int>
 1    14 female 9     not      Black or A…  NA      NA   never   0             4
 2    14 female 9     not      Black or A…  NA      NA   never   <NA>          2
 3    15 female 9     hispanic Native Haw…   1.73   84.4 never   30            7
 4    15 female 9     not      Black or A…   1.6    55.8 never   0             0
 5    15 female 9     not      Black or A…   1.5    46.7 did no… did no…       2
 6    15 female 9     not      Black or A…   1.57   67.1 did no… did no…       1
 7    15 female 9     not      Black or A…   1.65  132.  did no… <NA>          4
 8    14 male   9     not      Black or A…   1.88   71.2 never   <NA>          4
 9    15 male   9     not      Black or A…   1.75   63.5 never   <NA>          5
10    15 male   10    not      Black or A…   1.37   97.1 did no… <NA>          0
# … with 13,573 more rows, 3 more variables: hours_tv_per_school_day <chr>,
#   strength_training_7d <int>, school_night_hours_sleep <chr>, and abbreviated
#   variable names ¹​helmet_12m, ²​text_while_driving_30d, ³​physically_active_7d

set.seed(100)
n=1000
sample_means = rep(NA, n)
for(i in 1:n){
  sample_means[i] = mean(rnorm(100, mean=3.75, sd=9))
}
head(sample_means)

[1] 3.776213 3.850268 3.865138 3.000791 2.565257 4.866502

hist(sample_means, main = "", xlab = "Sample Means", col = "steelblue")

mean(sample_means)

[1] 3.764052

sd(sample_means)

[1] 0.8833878