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ケーススタディ:Rで都市の時系列データを分析する
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更新日 2026/01
RProbability & Statistics4時間12 ビデオ50 演習3,950 XP14,090修了証明書
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前提条件
Manipulating Time Series Data in R1
Flight Data
You've been hired to understand the travel needs of tourists visiting the Boston area. As your first assignment on the job, you'll practice the skills you've learned for time series data manipulation in R by exploring data on flights arriving at Boston's Logan International Airport (BOS) using xts & zoo.
2
Weather Data
In this chapter, you'll expand your time series data library to include weather data in the Boston area. Before you can conduct any analysis, you'll need to do some data manipulation, including merging multiple xts objects and isolating certain periods of the data. It's a great opportunity for more practice!
3
Economic Data
Now it's time to go further afield. In addition to flight delays, your client is interested in how Boston's tourism industry is affected by economic trends. You'll need to manipulate some time series data on economic indicators, including GDP per capita and unemployment in the United States in general and Massachusetts (MA) in particular.
4
Sports Data
Having exhausted other options, your client now believes Boston's tourism industry must be related to the success of local sports teams. In your final task on this project, your supervisor has asked you to assemble some time series data on Boston's sports teams over the past few years.
ケーススタディ:Rで都市の時系列データを分析する
コース完了 19百万人を超える学習者と共にケーススタディ:Rで都市の時系列データを分析するを始めましょう!
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