Project 37: One Prop Z-Interval

Suppose we want to estimate the proportion of students at a certain high school that are on TikTok.  We plan to construct a 90% confidence interval (confidence level = .9)

We randomly select 81 students in the high school and 27 claim they are on TikTok.

pHat = 27/81 = .333

sdPHat = sqrt(.333*.667/81) = .052

critical value = 1.65 (based on .9 confidence level)

margin of error = .052*1.65 = .086

confidence interval = [.333 - .086, .333 + .086] = [.247, .419]

We are 90% confident that the true proportion of students at this school that claim to be on TikTok is between .247 and .419.

Project 37: Variables 'x', 'n', 'confidenceLevel' have been initialized.  There are also working methods called normalcdf and invNorm.

x is the number of successes in the sample (27 in the example above)

n is the sample size (81 in the example above)

confidenceLevel is how confident we are in our interval (.9 in the example above)

Note: The confidence level is a number between 0 and 1 (not between 0 and 100 like a percentage)

Review projects 2-5 if you need a reminder of how normalcdf and invNorm work.

Task: Appropriately assign the values of 'lower' and 'upper' that represent the lower and upper bounds of the given confidence interval.

**If your code works for 5 test cases, you can enter your e-mail address

Universal Computational Math Methods:

pow(5,2) returns 25.0

abs(-3.0) returns 3

sqrt(49.0) returns 7.0