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Exercise

Understanding confidence intervals

In this exercise, you'll develop your intuition for how various parameter values impact confidence intervals. Specifically, you will explore through the get_ci() function how changes widen or tighten the confidence interval. This is the function signature, where cl is the confidence level and sd is the standard deviation. 

def get_ci(value, cl, sd):
  loc = sci.norm.ppf(1 - cl/2)
  rng_val = sci.norm.cdf(loc - value/sd)

  lwr_bnd = value - rng_val
  upr_bnd = value + rng_val 

  return_val = (lwr_bnd, upr_bnd)
  return(return_val)
Instructions 1/3
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  • 1

    Find the confidence interval with a value of 1, a confidence level of 0.975 and a standard deviation of 0.5.

  • 2

    Repeat the calculation, updating the confidence level to 0.95 and the standard deviation to 2. Leave the value as 1

  • 3

    Finally, update your code such that the standard deviation is 0.001 while leaving the confidence level and value the same as the previous exercise part. Compare the three confidence intervals outputted. How do they seem to relate to the parameters used?

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