RStudio for Six Sigma - Hypothesis Testing

提供方
Coursera Project Network
在此指導項目中,您將:

Import datasets into RStudio and Perform Hypothesis Testing

Understand and identify data types (continuous vs discrete). Choose the correct Hypothesis Testing tool.

Perform various Hypothesis Tests including Correlation, Regression, Logistic Regression, Chi-Square Test, T-Tests, Analysis of Variance (ANOVA), etc.

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

Welcome to RStudio for Six Sigma - Hypothesis Testing. This is a project-based course which should take approximately 2 hours to finish. Before diving into the project, please take a look at the course objectives and structure. By the end of this project, you will learn to identify data types (continuous vs discrete), understand what is Hypothesis Testing, pick the right Hypothesis Testing tool, perform various Hypothesis Tests including Correlation, Simple Regression, Logistic Regression, Chi-Square Test, T-Tests, Analysis of Variance (ANOVA), and Non-Parametric tests such as Wilcoxon Rank Sum and Kruskal Wallis.

您要培養的技能

  • Data Science
  • R Programming
  • Six Sigma
  • Statistical Hypothesis Testing
  • Rstudio

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. Perform hypothesis testing on Continous X and Y data in RStudio using Scatter Plot, Correlation, Regression.

  2. Perform hypothesis testing on Continuous X, Discrete Y data in RStudio using Logistic Regression.

  3. Perform hypothesis testing on Discrete X, Discrete Y data in RStudio using Chi-Square Test

  4. Perform hypothesis testing on Discrete X, Continuous Y data in RStudio. Analysis of Stability, Shape and Spread.

  5. Perform hypothesis testing on Discrete X, Continuous Y data in RStudio. 1 Sample t-Test, 2 Sample t-Test, ANOVA (Cont Y, Disc X), Non-parametric tests (Wilcoxon, Moods-Median, Kruskal)

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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