“Perhaps the best test of a man’s intelligence is his capacity for making a summary” — Lytton Strachey
Tips to Learn R using chatGPT : learning R can be challenging for beginners who may not have a strong background in statistics or programming.
Buy Statistics for Ecologists Using R and Excel (9781784271398) (9781784271404): Data Collection, Exploration, Analysis and Presentation: NHBS - Mark Gardener, Pelagic Publishing
From Wiki:"... the bottom and top of the box are always the 25th and 75th percentile (the lower and upper quartiles, respectively), and the band near the middle of the box is always the 50th percentile (the median). But the ends of the whiskers can represent several possible alternative values..."In R's default boxplot{graphics} code,upper whisker = min(max(x), Q_3 + 1.5 * IQR) lower whisker = max(min(x), Q_1 - 1.5 * IQR) where IQR = Q_3 - Q_1, the box length.So the upper whisker is located at the *smaller* of the maximum x value and Q_3 + 1.5 IQR, whereas the lower whisker is located at the *larger* of the smallest x value and Q_1 - 1.5 IQR. The range can be adjusted via argument range in boxplot() function, whose default value is 1.5. Here is what's described in the boxplot() document:rangethis determines how far the plot whiskers extend out from the box. If range is positive, the whiskers extend to the most extreme data point which is no more than range times the interquartile range from the box. A value of zero causes the whiskers to extend to the data extremes.Here is a full discussion about the whisker of boxplot in default R code:http://r.789695.n4.nabble.com/Whiskers-on-the-default-boxplot-graphics-td2195503.htmlHere is a useful plot from wikipedia for better understanding the boxplot by comparing the box plot against the probability density function (theoretical histogram) for a normal N(0,1σ2) distribution.
This article describes the various statistical measures of descriptive and inferential statistics to draw inferences from titanic data set
Beginning R: The Statistical Programming Language: R is a powerful, open-source programming language specifically designed for statistical computing and graphics.
The R programming language is a free and open source scripting language specialized for statistical computing and graphics.
When I first started using R, I really struggled to keep track of my scripts. Like many, I started by working directly in the R console. It makes it so hard to navigate, correct mistakes, and can be so frustrating that it almost made me stop learning. Discovering RStudio saved my data analysis career. It makes R fee...
The infograph 'Statistical Language Wars' compares statistical programming language like SAS, R and SPSS to see how they stack up.
Here we will analyze various factors such as immunization factors, mortality factors, economic factors, social factors, and other…
Ordinary Least Squares (OLS) produces the best possible coefficient estimates when your model satisfies the OLS assumptions for linear regression. However, if your model violates the assumptions, you might not be able to trust the results. Learn about the assumptions and how to assess them for your model.
Introduction Probability statistics and R though seemingly disparate, form a powerful trio in the world of data science and analysis.
Buy Applied Spatial Statistics and Econometrics: Data Analysis in R 1st Edition PDF ebook by author Katarzyna Kopczewska published by Routledge in 2021 and save up to 80% compared to the print version of this textbook. With PDF version of this textbook, not only save you money, you can also highlight, add text, underline add post-it notes, bookmarks to pages, instantly search for the major terms or chapter titles, etc. You can search our site for other versions of the Applied Spatial Statistics and Econometrics: Data Analysis in R 1st Edition PDF ebook. You can also search for others PDF ebooks from publisher Routledge, as well as from your favorite authors. We have thousands of online textbooks and course materials (mostly in PDF) that you can download immediately after purchase. Note: e-textBooks do not come with access codes, CDs/DVDs, workbooks, and other supplemental items. eBook Details: Full title: Applied Spatial Statistics and Econometrics: Data Analysis in R 1st Edition Edition: 1st Copyright year: 2021 Publisher: Routledge Author: Katarzyna Kopczewska ISBN: 9780367470777 Format: PDF Description of Applied Spatial Statistics and Econometrics: Data Analysis in R 1st Edition: This textbook is a comprehensive introduction to applied spatial data analysis, using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
Exploring Titanic Survival dataset in R and answering various statistical questions using t-test, chi-square test.
R is an open-source, statistical, and graphical programming language [1]. It is mainly popular due to its strength in writing software that utilizes statistical analyses, data visualization, and data mining. It has over 10,000 associated packages and over 2,000 free libraries that enhance its capabilities. Introduction to R Programming R is one of the most […]
A blog on statistics and R
Statistics can be used to share information. Sometimes the data is misleading. In this AP Statistics mini project students examine how data can be used to tell a story AND how that story can be incomplete. This is part of the AP Statistics curriculum. Included in this resource: Warm-up activity for misleading data Misleading data project guidelines Editable Rubric Answer key for activity This resource can be found in the following bundles: AP Statistics Curriculum AP Statistics Unit 1 Get students ready for the AP Statistics exam with the full curriculum. Questions? Leave your questions in the Q & A tab. This purchase is for one teacher only. This resource is not to be shared with colleagues or used by an entire grade level, school, or district without purchasing the proper number of licenses. If you are interested in a site license, please contact me for a quote. This resource may not be uploaded to the internet in any form for use beyond your class. This resource is for use with your students only.
This ultimate guide covers different correlation coefficients and tests for significance. Find out how to apply correlation analysis in R.
