This post is following of the above post.
In this post, I will get confidence interval for one proportion. In this case, number of nuclear power plants in Japan / number of nuclear power plants on earth.
First, I make a new dataframe to calculate the proportion.
Let's see data structure of mydf2.
Then, I add a new variable to indicate whether JPN or not.
I make bar chart to show how many nuclear power plants in Japan.
So, I see there are much less nuclear power plants in Japan compare to other countries total.
I calculate the proportion, the number of nuclear power plants in Japan / total number of nuclear power plants on the earth.
Above is using infer package specify() function and calculate() function.
Simple way is below.
So, I know 0.111( or 0.1107872) is the proportion.
I would like to calculate confidence interval for the proprtion, if it is random variable.
I make bootstrap distribution of it.
Let's visualize this distribution.
The vertical red line is observed proportion, 0.111.
Let's get confidence interval at 95% level.
The confidence interval is from 0.0782 to 0.146. It means that if I go to another multiverse world, I am 95% confident that Japan has 0.0782 to 0.146 proportion of nuclear power plants in the world.
Let's visualize this confidence interval.
That's it. Thank you!
Next post is
To read the 1st post,