np confidence interval
import numpy as np
import scipy.stats
def mean_confidence_interval(data, confidence=0.95):
a = 1.0 * np.array(data)
n = len(a)
m, se = np.mean(a), scipy.stats.sem(a)
h = se * scipy.stats.t.ppf((1 + confidence) / 2., n-1)
return m, m-h, m+hconfidence Interval
# confidence interval
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- confidence interval expresses a range of values within which we are pretty sure the population parameter lies. (how much sure? can be answer by confidence level)
- e.g. A 95% confidence interval says that for every 100 confidence intervals we calculate from sample data, about 95 of them will contain the population parameter and 5 will not.
# confidence level
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- how much sure? can be answer by confidence level
- It's like the bigger the butterfly catching net, the more confident you are to catch butterflies.
#misconception about confidence interval
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- This is NOT the interval that holds the 95% of data in the population.
- It is the interval that we are 95% confident will contain the true unknown value of population mean.
don't forget to upvote :)confidence interval
A 95% confidence interval says that if we run the study on 100 samples. 95 of them will have a value within the confidence interval.Copyright © 2021 Codeinu
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