## The power, and danger, of visualizations

August 7, 2013
By

I recently posted about visualizing the voting patterns of senators. In the post, I scraped voting data for each senator on every vote in the 113th Congress from the Senate website, and then assigned a code of 0 for a no vote on a particular issue, 1 ...

Read more »

## Are your data normal? Hint: no.

August 7, 2013
By

One of the frequently-asked questions over at the statistics subreddit (reddit.com/r/statistics) is how to test whether a dataset is drawn from a particular distribution, most often the normal distribution.There are standard tests for this sort of thin...

Read more »

## How to use the Autocorreation Function (ACF)?

August 7, 2013
By

The Autocorrelation function is one of the widest used tools in timeseries analysis. It is used to determine stationarity and seasonality. Stationarity: This refers to whether the series is “going anywhere” over time. Stationary series have a constant value over time. Below is what a non-stationary series looks like. Note the changing mean. And below […]

Read more »

## Trends in the Analytics Job Market

August 7, 2013
By

Tracking the job market for statistics, analytics, data mining and the like used to be a major undertaking. However, on November 10, 2011 the world’s largest web site for job postings, Indeed.com, released a tool that allows you to examine trends … Continue reading →

Read more »

## When you’re planning on fitting a model, build up to it by fitting simpler models first. Then, once you have a model you like, check the hell out of it

August 7, 2013
By

In response to my remarks on his online book, Think Bayes, Allen Downey wrote: I [Downey] have a question about one of your comments: My [Gelman's] main criticism with both books is that they talk a lot about inference but not so much about model building or model checking (recall the three steps of Bayesian […]The post When you’re planning on fitting a model, build up to it by fitting…

Read more »

## Simply Statistics #JSM2013 Picks for Wednesday

August 7, 2013
By

Sorry for the delay with my session picks for Wednesday. Here's what I'm thinking of: 8:30-10:20am: Bayesian Methods for Causal Inference in Complex Settings (CC-520a) or Developments in Statistical Methods for Functional and Imaging Data (CC-522bc) 10:30am-12:20pm: Spatial Statistics for Environmental Health Studies … Continue reading →

Read more »

## Stutter steps, and functional legends

August 7, 2013
By

Dona Wong asked me to comment on a project by the New York Fed visualizing funding and expenditure at NY and NJ schools. The link to the charts is here. You have to click through to see the animation. Here...

Read more »

## The power, and danger, of visualizations

August 7, 2013
By

I recently posted about visualizing the voting patterns of senators. In the post, I scraped voting data for each senator on every vote in the 113th Congress from the Senate website, and then assigned a code of 0 for a no vote on a particular issue, 1 for a yes vote, 2 for abstention, and 3 if the senator was not in office at the time of the vote (ie,…

Read more »

## Alternate ways to simulate multinomial data

August 7, 2013
By

My previous post described the multinomial distribution and showed how to generate random data from the multinomial distribution in SAS by using the RANDMULTINOMIAL function in SAS/IML software. The RANDMULTINOMIAL function is simple to use and implements an efficient algorithm called the sequential conditional marginal method (see Gentle (2003), p. [...]

Read more »

## JSM 2013 – Tuesday

August 7, 2013
By

The Joint Statistical Meeting in Montreal has proven to be very good.   Here are a few highlight from Tuesday’s sessions.  There is one major problem that exists and that is there are too many good sessions to attend.  During one time block I had six session that I wanted to go to.  Unfortunately, it […]

Read more »

## What Means Mean

August 7, 2013
By

Data is often reported as a single number. Unemployment rates, housing prices, crime, etc. are all boiled down to single numbers that average over a large population. But averages, or means, hide much of the richness of the underlying data, and without at least a sense of the spread of the data values, are largely meaningless.

Read more »

## What did Nate Silver just say? Blogging the JSM

August 6, 2013
By

Nate Silver gave his ASA Presidential talk to a packed audience (with questions tweeted[i]). Here are some quick thoughts—based on scribbled notes (from last night). Silver gave a list of 10 points that went something like this (turns out there were 11): 1. statistics are not just numbers 2. context is needed to interpret data […]

Read more »

## Cronbach to the future

August 6, 2013
By

One fascinating thing about working in the area of psychological statistics is how hard it is to move people away from reliance on bad, inefficient or otherwise problematic methods. My own view - informed to some extent by the literature, by experience...

Read more »

## JSM 2013 – Monday

August 6, 2013
By

I am currently attending the 2013 Joint Statistical Meeting in Montreal. I will try to share a few of the things that I take away each day. Last night (Monday) I attended the JSM keynote speaker with Nate Silver and it proved to be a very interesting discussion.  Silver is best known for his work […]

Read more »

## Read the source code

August 6, 2013
By

The other day, there was a bit of a twitter conversation about qqline in R. It made me think: how exactly is the line produced by qqline chosen? I seemed to recall that the line was through the first and third quartiles. An advantage of R is that you can just type the name of […]

Read more »

## G8 and Open Data

August 6, 2013
By

Open Data is a top priority now: G8 leaders signed the Open Data Charter on 18 June 2013. ‘The Open …Continue reading »

Read more »

## New words of 1917

August 6, 2013
By

I happened to come across a little book, “Current Glossary: Words Coined Since the War.” Here are some of them: as’pi-rin, n. A white compound used as a drug in the cure of headaches and rheumatism. bob’go, n. A kind of antelope in Africa; its meat is good for food. cat’ta-lo, n. A cross between […]The post New words of 1917 appeared first on Statistical Modeling, Causal Inference, and Social…

Read more »

## Create your own fine print

August 6, 2013
By

Note: The winner of the Book Quiz Round 2 was announced on my book blog. Congratulations to the winners. You can get your own copy of Numbersense here. *** A common advice for anyone living in the U.S. is "read...

Read more »

## Book quiz update, podcast

August 6, 2013
By

The second winner of the Book Quiz is Nancy, from Washington DC. Congratulations! Both winners wrote back saying they feel like buying a lottery ticket. The odds of winning that is much lower, be warned. *** Joe Dager, from Business901, and I chatted about Numbersense recently, and the interview will show up soon as a podcast. If you didn't see it last December, he did a very nice interview with…

Read more »

## Simply Statistics #JSM2013 Picks for Tuesday

August 6, 2013
By

It seems like Monday was a big hit at JSM with Nate Silver's talk and all. Rafa estimates that there were about 1 million people there (+/- 1 million). Ramnath Vaidyanathan has a nice summary of the talk and the Q&A … Continue reading →

Read more »

## Setting axes limits with googleVis

August 6, 2013
By

I posted about the various googleVis axis options for base charts, such as line, bar and area charts earlier, but I somehow forgot to mention how to set the axes limits.Unfortunately, there are no arguments such as ylim and xlim. Instead, the Google Ch...

Read more »

## Random Variables from a non-Parametric distribution know their limits

August 6, 2013
By
$Random Variables from a non-Parametric distribution know their limits$

You produce a non-parametric distribution. Then you obtain, say, 10 random variables (RV) from this non-parametric distribution- much the same way as you would obtain random variables from a (parametric) normal distribution with stated mean and variance. But unlike the parametric distribution, where our RVs would occur around the mean (our parameter), RVs from a […]

Read more »

## Google Developers R Programming Video Lectures

August 5, 2013
By

Google Developers recognized that most developers learn R in bits and pieces, which can leave significant knowledge gaps. To help fill these gaps, they created a series of introductory R programming videos. These videos provide a solid foundation for p...

Read more »

 Tweet

Email: