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Applied statistics for data analysis

Master the statistics every data analyst needs: describe your data rigorously, quantify uncertainty and make decisions with hypothesis tests. You will learn descriptive statistics, probability, sampling, confidence intervals, tests (t-test, chi-square, ANOVA), correlation and regression, applying everything with Python (scipy and statsmodels). It is the fifth course of the Professional Certificate in Data Analysis.

9 lessons 12 hours 900 XP

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Syllabus

Module 1 · Descriptive statistics

  1. 1Measures of central tendency50 min
  2. 2Measures of dispersion and outlier detection55 min
  3. 3Distributions and the normal distribution55 min

Module 2 · Probability and sampling

  1. 4Basic probability and Bayes' theorem55 min
  2. 5Sampling and the Central Limit Theorem55 min
  3. 6Confidence intervals55 min

Module 3 · Statistical inference

  1. 7Hypothesis testing and the t-test60 min
  2. 8Chi-square and ANOVA60 min

Module 4 · Relationships between variables

  1. 9Correlation and simple linear regression60 min

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