db5023

import scipy.stats as stats
import math

def one_sample_ztest_pop_proportion(tail, p, pbar, n, alpha):
    #Calculate test stat

    sigma = math.sqrt((p*(1-p))/(n))
    z = round((pbar - p) / sigma, 2)

    if tail == 'lower':

db5023

import scipy.stats as stats
import math

def one_sample_ttest_pval(tail, mu, x, s, n, alpha):

    #Calculate test statistic and p-value. Provide summary stats and specify 1 or 2 tailed test
    t = round((x - mu) / (s / math.sqrt(n)),2)
    test_stat = round(stats.t.ppf(q=alpha, 
            df=n-1),3)
    if tail == 1: