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Exercise

Normal distribution

On to the most recognizable and useful distribution of the bunch: the normal or Gaussian distribution. In the slides, we briefly touched on the bell-curve shape and how the normal distribution along with the central limit theorem enables us to perform hypothesis tests.

Similar to the previous exercises, here you'll start by simulating some data and examining the distribution, then dive a little deeper and examine the probability of certain observations taking place.

Instructions
100 XP
  • Generate the data for the distribution by using the rvs() function with size set to 1000; assign it to the data variable.
  • Display a matplotlib histogram; examine the shape of the distribution.
  • Given a standardized normal distribution, what is the probability of an observation greater than 2?
  • Looking at our sample, what is the probability of an observation greater than 2?
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