Comparing Proportions in R
Previously, we described the essentials of R programming and provided quick start guides for importing data into R. Additionally, we described how to compute descriptive or summary statistics, correlation analysis, as well as, how to compare sample means and variances using R software.
This chapter contains articles describing statistical tests to use for comparing proportions.
1 How this chapter is organized?
- One-Proportion Z-Test in R: Compare an Observed Proportion to an Expected One
- Two Proportions Z-Test in R: Compare Two Observed Proportions
- Chi-Square Goodness of Fit Test in R: Compare Multiple Observed Proportions to Expected Probabilities
- Chi-Square Test of Independence in R: Evaluate The Association Between Two Categorical Variables
2 One-proportion z-Test
Compare an observed proportion to an expected one.
Read more: —> One-Proportion Z-Test in R.
4 Chi-square goodness of fit test in R
Compare multiple observed proportions to expected probabilities.
Read more: —> Chi-square goodness of fit test in R.
5 Chi-Square test of independence in R
Evaluate the association between two categorical variables.
Read more: —> Chi-Square Test of Independence in R.
6 See also
7 Infos
This analysis has been performed using R statistical software (ver. 3.2.4).
Enjoyed this article? I’d be very grateful if you’d help it spread by emailing it to a friend, or sharing it on Twitter, Facebook or Linked In.
Show me some love with the like buttons below... Thank you and please don't forget to share and comment below!!
Show me some love with the like buttons below... Thank you and please don't forget to share and comment below!!
Avez vous aimé cet article? Je vous serais très reconnaissant si vous aidiez à sa diffusion en l'envoyant par courriel à un ami ou en le partageant sur Twitter, Facebook ou Linked In.
Montrez-moi un peu d'amour avec les like ci-dessous ... Merci et n'oubliez pas, s'il vous plaît, de partager et de commenter ci-dessous!
Montrez-moi un peu d'amour avec les like ci-dessous ... Merci et n'oubliez pas, s'il vous plaît, de partager et de commenter ci-dessous!
Recommended for You!
Recommended for you
This section contains the best data science and self-development resources to help you on your path.
Books - Data Science
Our Books
- Practical Guide to Cluster Analysis in R by A. Kassambara (Datanovia)
- Practical Guide To Principal Component Methods in R by A. Kassambara (Datanovia)
- Machine Learning Essentials: Practical Guide in R by A. Kassambara (Datanovia)
- R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia)
- GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia)
- Network Analysis and Visualization in R by A. Kassambara (Datanovia)
- Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia)
- Inter-Rater Reliability Essentials: Practical Guide in R by A. Kassambara (Datanovia)
Others
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham & Garrett Grolemund
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Géron
- Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce & Andrew Bruce
- Hands-On Programming with R: Write Your Own Functions And Simulations by Garrett Grolemund & Hadley Wickham
- An Introduction to Statistical Learning: with Applications in R by Gareth James et al.
- Deep Learning with R by François Chollet & J.J. Allaire
- Deep Learning with Python by François Chollet
Get involved :
Click to follow us on Facebook :
Comment this article by clicking on "Discussion" button (top-right position of this page)
Click to follow us on Facebook :
Comment this article by clicking on "Discussion" button (top-right position of this page)
Articles contained by this category :
Chi-square Goodness of Fit Test in R
Chi-Square Test of Independence in R
One-Proportion Z-Test in R
Two-Proportions Z-Test in R