An example from healthcare is used to show that a single graph can be acceptable by itself but confusing or even misleading when placed in a group of graphs.

January 8, 2014

By Naomi RobbinsNovember 27, 2013

By Naomi RobbinsFebruary 12, 2013

By Naomi RobbinsFebruary 5, 2013

By Naomi RobbinsFebruary 4, 2013

By Naomi RobbinsNewspapers are expected to check facts and report accurately. Why, then, should they not also be expected to check their charts and graphs and ensure that they are accurate. Figure 1 appears on page 13 of the February 4, 2013 issue of NJBIZ. My measurements show that the green square is about 9% of the […]

January 18, 2013

By Naomi RobbinsJanuary 15, 2013

By Naomi RobbinsJanuary 10, 2013

By Naomi RobbinsJanuary 9, 2013

By Naomi RobbinsJanuary 3, 2013

By Naomi Robbins- Access to Statistics
- Adventures in Analytics and Visualization
- Adventures in R
- All Things R
- Analysis with Programming
- analyze stuff
- Asymptotically Unbiased
- bayesianbiologist » Rstats
- Big Data, Plainly Spoken (aka Numbers Rule Your World)
- BioStatMatt » statistics
- BioStatProf
- Blog about Stats
- blog.RDataMining.com
- Bot Thoughts
- Burns Statistics
- Carlisle Rainey » Methods/Statistics
- CoolStatsBlog
- dahtah
- Darren Wilkinson’s research blog
- Data Miners Blog
- Data Mining – Blog.com
- Data Mining: Text Mining, Visualization and Social Media
- Data, Evidence, and Policy – Jared Knowles
- DiffusePrioR
- Doing Bayesian Data Analysis
- eagereyes
- Econometrics Beat: Dave Giles’ Blog
- Econometrics by Simulation
- Effective Graphs
- Engaging Market Research
- Error Statistics Philosophy » Statistics
- Fiddling with data and code
- FishyOperations » R
- Freakonometrics » Statistics
- Getting Genetics Done
- Gianluca Baio’s blog
- Graph of the Week
- Honglang Wang’s Blog
- Hyndsight
- I say things
- information aesthetics
- John D. Cook » Statistics
- Junk Charts
- Learn and Teach Statistics and Operations Research
- Learning From Data » Statistics
- Lindons Log » Statistics
- Machine Master
- mages’ blog
- Nicebread
- No Hesitations
- Normal Deviate
- NumberTheory » R stuff
- On the lambda » On the lambda
- One R Tip A Day
- Point Mass Prior
- Political Methodology
- Portfolio Probe » R language
- Probably Overthinking It
- Psychological Statistics
- Publishable Stuff
- Quantum Forest » rblogs
- R Chronicle
- R snippets
- R Tutorial
- r4stats.com
- rbresearch » R
- Realizations in Biostatistics
- SAS and R
- SAS Programming for Data Mining
- Serious Stats
- Sharp Statistics
- Simply Statistics
- Stat Bandit
- statalgo
- Statisfaction » R
- Statisfaction » Statistics
- Statistical Modeling, Causal Inference, and Social Science
- Statistical Research
- Systematic Investor » R
- The Analysis Factor
- The Chemical Statistician » Statistics
- The Data Game – Ilan Man
- The DO Loop
- The R Trader
- The stupidest thing… » R
- The stupidest thing… » Statistics
- Three-Toed Sloth
- TRinker’s R Blog
- TRinker’s Stats Blog
- Vik Paruchuri
- Wiekvoet
- Will Lowe
- Win-Vector Blog » Statistics
- Xi’an’s Og » R
- Yihui Xie

- This is what “power = .06” looks like. Get used to it.
- Guys, we need to talk. (Houston, we have a problem).
- Orthogonal Regression: First Steps
- Nominal, Ordinal, Interval, Schmordinal
- SAS PROC MCMC example in R; Poisson Regression
- The difference between RUN and CALL for SAS/IML subroutines
- rmarkdown: Alter Action Depending on Document
- Empirical Likelihood meets Bayesian Analysis
- Example 2014.13: Statistics doesn't have to be so hard! Resampling in R and SAS
- Le Monde puzzle [#887bis]