def sample_mean(data, sample_size):
total = 0
sample = getSample(data, sample_size)
num_values = len(sample)
for num in sample:
total = addition(total, num)
return division(total, num_values)
def sample_mean(data, sample_size):
total = 0
# check that get sample returns the proper number of samples
# check that sample size is not 0
# check that sample size is not larger than the population
# https://realpython.com/python-exceptions/
# https://stackoverflow.com/questions/129507/how-do-you-test-that-a-python-function-throws-an-exception
sample = getSample(data, sample_size)
num_values = len(sample)
for num in sample:
total = addition(total, num)
return division(total, num_values)
def sample_st_deviation(data, sample_size):
dev = 0
sample = getSample(data, sample_size)
sample_values = len(sample)
x_bar = sample_mean()
x = sample_values
n = subtraction(sample_values, 1)
for dev in sample:
dev = subtraction(x, x_bar)
square_x_bar = square(dev)
add = addition(square_x_bar, square_x_bar)
divide = division(add, n)
return squareroot(divide)
def ssd(data):
total = 0
sample = random.randint(1, len(data))
new_sample = getSample(data, sample)
new_mean = mean(new_sample)
for numb in new_sample:
result = subtraction(numb, new_mean)
sq = squaree(result)
total = addition(total, sq)
n = len(new_sample)
d = division(subtraction(1, n), total)
samp_sd = squar_rot(d)
# actual_sd = statistics.stdev(new_sample)
return samp_sd