Box Plots

A Box Plot is a statistical graph that is used to depict groups of numerical data through their quartiles. Coursera's Box Plots skill catalogue teaches you about the fundamentals and applications of this impressive data visualization tool. You'll learn how to construct box plots, interpret data from box plots, and understand complex data distributions to identify outliers and variances. This will help you develop your analytical thinking skills, enhance your data interpretation abilities, and make informed decisions based on statistical data. You'll also be equipped to apply these skills in fields such as data science, research analysis, and business intelligence.
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Results for "box plots"

  • Skills you'll gain: Sampling (Statistics), Statistical Methods, Descriptive Statistics, Statistical Visualization, Data Import/Export, Pareto Chart, Histogram, Statistical Analysis, R (Software), Box Plots, R Programming, Data Synthesis, Probability Distribution, Probability & Statistics, Exploratory Data Analysis, Statistics, Statistical Hypothesis Testing, Data Science

  • Coursera Project Network

    Skills you'll gain: Matplotlib, Seaborn, Exploratory Data Analysis, Data Visualization, Pandas (Python Package), Plot (Graphics), Statistical Visualization, Data Visualization Software, Scatter Plots, Data Analysis, Box Plots, Python Programming

  • Status: Preview

    Skills you'll gain: Matplotlib, Plot (Graphics), Statistical Visualization, Data Visualization Software, Scientific Visualization, Interactive Data Visualization, Scatter Plots, Jupyter, Histogram, Box Plots, Graphing, Computer Programming, Integrated Development Environments, Animations

  • Status: Free Trial

    Skills you'll gain: Rmarkdown, Plot (Graphics), Ggplot2, Statistical Visualization, Box Plots, Scatter Plots, Data Visualization, Histogram, Descriptive Statistics, Data Visualization Software, Graphing, R Programming, Data Science

  • Status: Free Trial

    University of Colorado Boulder

    Skills you'll gain: Data-Driven Decision-Making, Probability Distribution, Descriptive Statistics, Data Analysis, Data Visualization, R (Software), Box Plots, Statistical Methods, Data Manipulation, Probability, Statistical Analysis, Histogram

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