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Learning Statistics with Python

Paired t-test

The following function conducts a paired t-test:

This process resembles the one used for independent samples, but here we do not need to check the homogeneity of variance. The paired t-test explicitly does not assume that variances are equal.

Keep in mind that for a paired t-test, it's crucial that the sample sizes are equal.

With this information in mind, you can proceed to the task of conducting a paired t-test.

Here, you have data regarding the number of downloads for a particular app. Take a look at the samples: the mean values are nearly identical.

Task

We establish the hypotheses:

  • H₀: The mean number of downloads before and after the changes is the same;
  • Hₐ: The mean number of downloads is greater after the modifications.

Conduct a paired t-test with this alternative hypothesis, using before and after as the samples.

Everything was clear?

Section 6. Chapter 8
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course content

Course Content

Learning Statistics with Python

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 ValueDescriptive Statistics Quiz

2. Mean, Median and Mode with Python

Examine the DatasetCalculating Mean and Median Values with PythonStatistics with pandasCalculate the Mean and Median Salary

3. Variance and Standard Deviation

Population VarianceSample VarianceCalculate Variance with PythonStandard deviationStandard Deviation with PythonCalculating Variance and Standard Deviation

4. Covariance vs Correlation

CovarianceCorrelationSelect All Possible ValuesCalculate Covariance and Correlation

5. Confidence Interval

Explore the Data SetConfidence IntervalCalculating Confidence Interval with PythonConfidence Interval Width QuizCalculate 95% Confidence IntervalAdvanced Confidence Interval Calculation with PythonMatch the Functions

6. Statistical Testing

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

Paired t-test

The following function conducts a paired t-test:

This process resembles the one used for independent samples, but here we do not need to check the homogeneity of variance. The paired t-test explicitly does not assume that variances are equal.

Keep in mind that for a paired t-test, it's crucial that the sample sizes are equal.

With this information in mind, you can proceed to the task of conducting a paired t-test.

Here, you have data regarding the number of downloads for a particular app. Take a look at the samples: the mean values are nearly identical.

Task

We establish the hypotheses:

  • H₀: The mean number of downloads before and after the changes is the same;
  • Hₐ: The mean number of downloads is greater after the modifications.

Conduct a paired t-test with this alternative hypothesis, using before and after as the samples.

Everything was clear?

Section 6. Chapter 8
toggle bottom row
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