Menafsirkan scatter plot

Scatter plot memungkinkan Anda mengeksplorasi hubungan antara dua variabel kontinu.

Di sini Anda dapat melihat scatter plot harapan hidup rata-rata (pada sumbu y) dibandingkan dengan rata-rata lama sekolah (pada sumbu x) untuk negara-negara di seluruh dunia. Setiap titik pada plot mewakili satu negara. Garis tren lurus dari model regresi linear ditampilkan.

A scatter plot of average life expectancy versus average length of schooling, with a linear trend line.

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Sumber data: United Nations

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Memahami Visualisasi Data

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In this chapter you’ll learn the value of visualizations, using real-world data on British monarchs, Australian salaries, Panamanian animals, and US cigarette consumption, to graphically represent the spread of a variable using histograms and box plots.

Exercise 1: A plot tells a thousand words Exercise 2: Motivating visualization Exercise 3: Continuous vs. categorical variables Exercise 4: Histograms Exercise 5: Interpreting histograms Exercise 6: Adjusting bin width Exercise 7: Box plots Exercise 8: Interpreting box plots Exercise 9: Ordering box plots

You’ll learn how to interpret data plots and understand core data visualization concepts such as correlation, linear relationships, and log scales. Through interactive exercises, you’ll also learn how to explore the relationship between two continuous variables using scatter plots and line plots. You'll explore data on life expectancies, technology adoption, COVID-19 coronavirus cases, and Swiss juvenile offenders. Next you’ll be introduced to two other popular visualizations—bar plots and dot plots—often used to examine the relationship between categorical variables and continuous variables. Here, you'll explore famous athletes, health survey data, and the price of a Big Mac around the world.

Exercise 1: Scatter plot Exercise 2: Menafsirkan scatter plot

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Exercise 3: Tren dengan scatter plot Exercise 4: Line plot Exercise 5: Menafsirkan plot garis Exercise 6: Skala logaritmik untuk line plot Exercise 7: Diagram batang Exercise 8: Menafsirkan bar plot Exercise 9: Menafsirkan stacked bar plot Exercise 10: Dot plot Exercise 11: Menafsirkan dot plot Exercise 12: Mengurutkan dot plot

It’s time to make your insights even more impactful. Discover how you can add color and shape to make your data visualizations clearer and easier to understand, especially when you find yourself working with more than two variables at the same time. You'll explore Los Angeles home prices, technology stock prices, math anxiety, the greatest hiphop songs, scotch whisky preferences, and fatty acids in olive oil.

Exercise 1: Higher dimensions Exercise 2: Another dimension for scatter plots Exercise 3: Another dimension for line plots Exercise 4: Using color Exercise 5: Eye-catching colors Exercise 6: Qualitative, sequential, diverging Exercise 7: Highlighting data Exercise 8: Plotting many variables at once Exercise 9: Interpreting pair plots Exercise 10: Interpreting correlation heatmaps

In this final chapter, you’ll learn how to identify and avoid the most common plot problems. For example, how can you avoid creating misleading or hard to interpret plots, and will your audience understand what it is you’re trying to tell them? All will be revealed! You'll explore wind directions, asthma incidence, and seats in the German Federal Council.

Exercise 1: Polar coordinates Exercise 2: Pie plots Exercise 3: Rose plots Exercise 4: Axes of evil Exercise 5: Bar plot axes Exercise 6: Dual axes Exercise 7: Sensory overload Exercise 8: Chartjunk Exercise 9: Multiple plots Exercise 10: Congratulations