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for the rest of this question, suppose you decide to use the number of times you see the area code 617 in 50 spam calls as your test statistic. question 5. write a function called simulate that generates exactly one simulated value of your test statistic under the null hypothesis. it should take no arguments and simulate 50 area codes under the assumption that the result of each area is sampled from the range 200-999 inclusive with equal probability. your function should return the number of times you saw the 617 area code in those 50 random spam calls.

Respuesta :

visited_test_stats_under_null = make_array()

repeat = 20000

for i in np.arrange(repetitions):

 new_sum_of_area_code = simulate_visited_area_codes()

 visited_test_stats_under_null = np.append(visited_test_stats_under_null, new_sum_of_area_code)

visited_test_stats_under_null( )

What is a null hypothesis?

Two possibilities being the same is the null hypothesis in inferential statistics. That the observed difference is solely the result of chance is the null hypothesis. Calculating the probability that the null hypothesis is correct using statistical tests is possible.

The null hypothesis can be tested in order to determine whether or not two measured phenomena are related. This makes the null hypothesis useful. It can tell a user if the outcomes are the result of chance or deliberate manipulation of a phenomenon.

To learn more about null hypothesis, use the link given
https://brainly.com/question/13770153
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