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.

Sebuah plot menyampaikan seribu kata

Memotivasi visualisasi

Opsi

kontinu

kategorikal

Variabel kontinu vs. kategorikal

Histogram

Benar

Salah

Menafsirkan histogram

Menyesuaikan lebar bin

Plot kotak

Menafsirkan box plot

Mengurutkan box plot

Visualizing distributions

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.

Scatter plots

Interpreting scatter plots

Trends with scatter plots

Line plots

Interpreting line plots

Logarithmic scales for line plots

Bar plots

Interpreting bar plots

Interpreting stacked bar plots

Dot plots

Interpreting dot plots

Sorting dot plots

Visualizing two variables

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.

Higher dimensions

Another dimension for scatter plots

Another dimension for line plots

Using color

Eye-catching colors

Qualitative, sequential, diverging

Highlighting data

Plotting many variables at once

Interpreting pair plots

Interpreting correlation heatmaps

The color and the shape

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.

Polar coordinates

Pie plots

Rose plots

Axes of evil

Bar plot axes

Dual axes

Sensory overload

Chartjunk

Multiple plots

Congratulations

99 problems but a plot ain't one of them

Memvisualisasikan data menggunakan bagan, grafik, dan peta adalah salah satu cara paling efektif untuk mengomunikasikan data yang kompleks. Dalam kursus ini, Anda akan mempelajari cara memilih visualisasi terbaik untuk himpunan data Anda, serta cara menafsirkan jenis plot umum seperti histogram, scatter plot, line plot, dan bar plot. Anda juga akan mempelajari praktik terbaik dalam penggunaan warna dan bentuk pada plot, serta cara menghindari kesalahan umum. Melalui latihan praktis, Anda akan menjelajahi lebih dari 20 himpunan data secara visual, termasuk harapan hidup global, harga rumah di Los Angeles, 100 atlet paling terkenal versi ESPN, dan lagu hip-hop terbaik sepanjang masa.

Video dilengkapi transkrip langsung, yang dapat diakses dengan mengeklik "Show transcript" di kiri bawah video.

Glosarium kursus dapat ditemukan di sebelah kanan pada bagian sumber daya.

Untuk memperoleh kredit CPE, Anda harus menyelesaikan kursus dan meraih skor 70% pada penilaian yang memenuhi syarat. Anda dapat menuju penilaian dengan mengeklik ajakan kredit CPE di sebelah kanan.

Pelajari cara memvisualisasikan data dengan grafik dan peta serta cara menginterpretasikan waktu plot.

Variabel kontinu vs. kategorikal

Memahami Visualisasi Data

Latihan interaktif praktis