jiaweih

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    "## Scalar"
   ]
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jiaweih

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jiaweih

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jiaweih

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jiaweih

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jiaweih

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jiaweih

# Enter your code here. Read input from STDIN. Print output to STDOUT

import sys
import math

def get_std(lst):
    length = len(lst)
    summ = sum(lst)
    average = reduce(lambda x, y: x + y, lst) / length
    std = 0

jiaweih

import numpy as np

old_lst = [1,2,3]
old_std = round(np.std(old_lst),3)
N = []

for i in np.arange(0,50.0,0.0001):
    new_lst = old_lst + [i]
    new_std = np.std(new_lst)
    if np.abs(new_std - old_std) < 0.0001:

jiaweih

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    "> It is useful to have a single measure of exposure for each risk factor whether the risk is   dichotomous, polytomous or continuous. This allows examination of trends in risk factors over time. An age-standardized version allows for comparison between places that highlights differences in exposure"
   ]
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jiaweih

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