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Exercise

Calculating a z-score

Since variables have arbitrary ranges and units, we need to standardize them. For example, a hypothesis test that gave different answers if the variables were in Euros instead of US dollars would be of little value. Standardization avoids that.

One standardized value of interest in a hypothesis test is called a z-score. To calculate it, you need three numbers: the sample statistic (point estimate), the hypothesized statistic, and the standard error of the statistic (estimated from the bootstrap distribution).

The sample statistic is available as late_prop_samp.

late_shipments_boot_distn is a bootstrap distribution of the proportion of late shipments, available as a list.

pandas and numpy are loaded with their usual aliases.

Instructions

100 XP
  • Hypothesize that the proportion of late shipments is 6%.
  • Calculate the standard error from the standard deviation of the bootstrap distribution.
  • Calculate the z-score.