/Statistical-Inference-using-Python

Coursera Statistical Inference using Python - Exercises and Assignments

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Statistical Inference using Python

Coursera Statistical Inference using Python - Exercises and Assignments

Inferential Statistic:

Inferential Statistics enables you to make an educated guess about a population parameter based on a statistic computed from a sample randomly drawn from that population.

Parameter - is about Population
Statistic - is about Sample

Confidence Intervals

  • One Proportion:

Only one proportion of the population is considered.

Estimating a Population Proportion with Confidence:

Best Estimate = Unbiased Point Estimate = Sample Proportion()

Margin of Error = "a few" Estimated Standard Error
"a few" is a multiplier from appropriate distribution based on desired confidence level.eg: , (Student's t-test)

95% Confidence Interval Calculation for one Population Proportion:

With Confidence Intervals, we can conclude that, in the multiple sample iterations caclulating the confidence interval for each sample, about 95% of such confidence intervals will contain the true population proportion

  • Different z^{\star} multiplers for different confidence intervals
    90% CI - 1.645
    95% CI - 1.96
    98% CI - 2.326
    99% CI - 2.576

Therefore, More Confident ==> Larger Multipler ==> Wider Interval