Regression Analysis

Demographic Data Analysis

This free project is part of the liveProject series Regression for Life Expectancy Analysis.
prerequisites
intermediate Python • basics of statistics (regression analysis) • basics of NumPy and pandas
skills learned
reading, cleaning, and merging data with pandas • exploring data for trends and distributions • doing data visualizations with Matplotlib and Seaborn
Monica Guimaraes
1 week · 8-10 hours per week · INTERMEDIATE
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This free project is part of the liveProject series Regression for Life Expectancy Analysis. explore series
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In this liveProject, you’ll use the Python data ecosystem to explore how demographic data affects American life expectancy. You’ll use pandas and NumPy to clean and merge a newly collected data set Matplotlib, and seaborn to create a variety of plots that showcase the distribution of the data and expose the relationships between the variables.

project author

Monica Guimaraes
Monica Guimaraes has more than fifteen years of experience organizing and teaching undergraduate courses in automata theory, numerical analysis, programming languages, and statistics. Her passion for artificial intelligence goes back to her college years, having done her thesis in automatic-theorem-proving and working later as an AI researcher. She also has extensive experience in software development in corporations.

prerequisites

This liveProject is for confident Python programmers. To begin this liveProject you will need to be familiar with:

TOOLS
  • Intermediate Python
  • Basics of pandas
  • Basics of NumPy
  • Basic Jupyter Notebook
TECHNIQUES
  • Basics of Python data analysis

you will learn

In this liveProject, you’ll learn vital skills for planning and orchestrating a data analysis project. These foundational skills are easy to transfer to almost any data undertaking.

  • Reading, cleaning and merging newly collected data with pandas
  • Exploring data for trends and distributions
  • Building data visualizations with Matplotlib and seaborn

features

Self-paced
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