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Learn Statistics with Python

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Overview

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Statistics is a powerful tool for analyzing and interpreting data. This course covers key descriptive statistics, including mean, median, mode, standard deviation, and variance. You'll learn how to calculate these metrics and interpret their significance, enabling you to describe and analyze datasets effectively.

Syllabus

  • Mean, Median, and Mode: Learn to use Python packages or manually calculate the mean, median, and mode of real-world datasets.
    • Lesson: Mean
    • Lesson: Median
    • Lesson: Mode
    • Project: Central Tendency for Housing Data
    • Quiz: Mean, Median, and Mode
  • Variance and Standard Deviation: In this module, you will learn how to quantify the spread of the dataset by calculating the variance and standard deviation.
    • Lesson: Variance
    • Lesson: Standard Deviation
    • Quiz: Variance and Standard Deviation
    • Project: Variance in Weather
  • Histograms: In this lesson, learn how to visualize and interpret a dataset using a histogram.
    • Lesson: Histograms
    • Project: Traveling to Acadia
    • Quiz: Histograms
  • Describe a Histogram: Learn how to describe a statistical distribution by considering its center, shape, spread, and outliers.
    • Lesson: Describe a Histogram
    • Project: Describe Exam Grade Distributions
    • Quiz: Describe a Histogram
  • Quartiles, Quantiles, and Interquartile Range: In this course, you will learn how to calculate three important descriptive statistics that describe the spread of the data.
    • Lesson: Quartiles
    • Lesson: Quantiles
    • Lesson: Interquartile Range
    • Quiz: Quantiles, Quartiles, and IQR
    • Project: Life Expectancy By Country
  • Boxplots: Learn how to create and interpret boxplots using a variety of different datasets
    • Lesson: Boxplots
    • Quiz: Boxplots
    • Project: Healthcare in Different States

Taught by

Kenny Lin

Reviews

4.6 rating at Codecademy based on 82 ratings

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