FAQ: One-Sample T-Tests in SciPy - Review

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1

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This community-built FAQ covers the “Review” exercise from the lesson “One-Sample T-Tests in SciPy”.

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This exercise can be found in the following Codecademy content:

Master Statistics with Python

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2

for the last exercise, how would the for loop look like?

  1. Run the same hypothesis tests for days 1-10 (the fastest way to do this is with a for-loop!) and print out the resulting p-values. What’s the smallest p-value you observe for those 10 days?

  2. Try changing the null hypothesis so that the expected population mean that you’re testing against is different from 1000. Try any numbers that you want. How do your p-values change?

3

Mine loop looks like this @byte7345305615

from scipy.stats import ttest_1samp
import numpy as np

daily_prices = np.genfromtxt("daily_prices.csv", delimiter=",")
for i in range(10):
  tstat, pval = ttest_1samp(daily_prices[i], 1000)
  print(f'Mean is equal to {np.mean(daily_prices[i])} and p is equal to {pval}')
4

Hi there,

So we can say that the lowest p-value found on day 6, which is 0.018 (1.8%), for the null hypothesis being true that the average price on each day is 1000 rupees, is unlikely and probably that the average price on that day was different?

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