Building and analyzing linear regression model in R

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Coursera Project Network
在此指導項目中,您將:

Learn how to load and clean a real world dataset in R.

Learn how to build a linear regression model and various plots to analyze the model’s performance.

Learn how to predict future values using the model and calculate model error metrics.

Clock1.5 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

By the end of this project, you will learn how to build and analyse linear regression model in R, a free, open-source program that you can download. You will learn how to load and clean a real world dataset. Next, you will learn how to build a linear regression model and various plots to analyze the model’s performance. Lastly, you will learn how to predict future values using the model. By the end of this project, you will become confident in building a linear regression model on real world dataset and the know-how of assessing the model’s performance using R programming language. Linear regression models are useful in identifying critical relationships between predictors (or factors) and output variable. These relationships can impact a business in the future and can help business owners to make decisions. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

您要培養的技能

Linear RegressionMachine LearningR ProgrammingRstudio

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Load a real world dataset and summarize it in R

  2. Clean your dataset

  3. Split your dataset into training and test set

  4. Build linear regression model and interpret model summary statistics

  5. Plot and analyze model residuals

  6. Predict future values and calculate model error metrics

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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