course content

Course Content

Learning Statistics with Python

1. Basic Concepts

Sample vs PopulationTypes of StatisticsTypes of DataMean ValueMedian ValueMedian Value of the Even Number of ValuesMean or MedianMode ValueChallenge

2. Mean, Median and Mode with Python

Examine the DatasetCalculate Mean and Median Values with PythonStatistics with pandasChallenge

3. Variance and Standard Deviation

Population VarianceSample VarianceCalculate Variance with PythonStandard deviationStandard Deviation with PythonChallenge

4. Covariance vs Correlation

CovarianceCorrelationChallenge 1Challenge 2

5. Confidence Interval

Explore the Data SetConfidence IntervalCalculating Confidence Interval with PythonChallenge 1Challenge 2Calculating Confidence Interval with PythonChallenge

6. Statistical Testing

What is t-testHypothesest-test MathematicallyOne-Tailed And Two-Tailed Testt-test AssumptionsPerforming a t-test in PythonChallengePaired t-test

Learning Statistics with Python

Calculating Confidence Interval with PythonCalculating Confidence Interval with Python

If we are working with a small distribution (size less than or equal to 30) that approximates the normal distribution, we will use t-statistics.

How to calculate the confidence interval?

  • We use the t.interval() function from scipy.stats for the Student's T distribution.
  • As mentioned earlier, alpha represents the confidence level.
  • df stands for the number of degrees of freedom.
  • loc represents the mean.
  • sem represents the standard error of the sample.

Degrees of Freedom

Degrees of freedom are the number of independent information elements used to estimate a parameter.

The formula for degrees of freedom is N - 1, where N is the sample size.

Feel free to adjust the alpha parameter and observe the resulting changes.

Everything was clear?

Section 5. Chapter 6