randalolson.com: 144 years of marriage and divorce in 1 chart

randalolson.com: 144 years of marriage and divorce in 1 chart

It’s fascinating to see the effects of WWI and WWII on marriage and divorce rates in the United States. At the beginning of America’s entry into WWI (1917) and WWII (1941), we see notable spikes in marriage rates as the young conscripts rushed to the altar thinking it would be the last time they would see their lover.

Similarly, after the conclusion of WWI (1918) and WWII (1945), those same young men and women coming back from the war seemed eager to elope and start a new life after spending years experiencing the destructive nature of war. Interestingly, the only notable spike in divorce rates in the past 144 years also followed the conclusion of WWII, likely due to many of the pre-WWII marriages coming to an abrupt end once the romance of wartime marriage wore off.

The most notable drop in marriage rates occurred during The Great Depression in the early 1930s, with a sudden 25% drop in marriage rates during America’s greatest time of hardship. It seems when Americans fall on hard times, marriage is one of the first things to take the back seat.

One particularly confusing aspect of this data set was the fact that the post-war era in the 1950s and 1960s seemed to experience a significant drop in marriage rates, despite the fact that the 1950s and 1960s were known as a time of nearly-universal marriage in the U.S.

With the raw counts in hand, the explanation for the drop in per capita marriage rates becomes abundantly clear: People weren’t marrying less in the 1950s and 1960s, but the surge of newborn children during the Baby Boom artificially decreases the per capita rates. Once the Baby Boomers came of age in the 1970s, marriage rates returned to pre-WWII levels — barring a slight drop in marriages during the dramatic conclusion of the Vietnam War (1975).

Looking to more recent history, there has been a steady decline in marriage rates (and consequently, divorce rates) since the 1980s, with no sign of slowing down. In fact, when taking population into account, marriage rates in the U.S. are now at the lowest they’ve ever been in recorded U.S. history — even lower than during The Great Depression!

If you think you know why marriage rates have been declining in the U.S. since the 1980s, I’d be curious to hear your theories in the comments.

onecoolsitebloggingtips.com: New Stats Page Feedback

onecoolsitebloggingtips.com: New Stats Page Feedback

There are two old Stats pages and they are both available from the classic dashboard. You can go directly to the classic dashboard by logging in here:https://wordpress.com/wp-login.php?.

The old Stats pages are

1. https://YourWeirdWebsiteName.wordpress.com/wp-admin/index.php?page=stats (really old, “classic”). Link is found in the dashboard admin panel in the “Dashboard” drop-down menu (clock symbol).

2. https://wordpress.com/my-stats/ (kinda old, “super classic”). The link is found in the dashboard navigation menu, in the website title drop-down menu.

Professor Rob J Hyndman

Professor Rob J Hyndman
Rob J Hyndman is Professor of Statistics in the Department of Econometrics and Business Statistics at Monash University and Director of the Monash University Business & Economic Forecasting Unit. He is also Editor-in-Chief of the International Journal of Forecasting and a Director of the International Institute of Forecasters. Rob is the author of over 100 research papers in statistical science. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research, especially in the area of statistical forecasting. For 25 years, Rob has maintained an active consulting practice, assisting hundreds of companies and organizations. His recent consulting work has involved forecasting electricity demand, tourism demand, the Australian government health budget and case volume at a US call centre.

John Myles White: “He who refuses to do arithmetic is doomed to talk nonsense.”

John Myles White: “He who refuses to do arithmetic is doomed to talk nonsense.”
This term, I’ve been sitting in on Rene Carmona’s course on Modern Regression and Time Series Analysis. Much of the material on regression covered in the course was familiar to me already, but I’ve never felt that I had a real command of times series analysis methods. When Carmona defined the AR(p) model in class a few weeks ago, it struck me that, though I’d seen the defining equation several times before, I’d never realized earlier that the AR(p) model subsumes all possible linear recurrence relations. Also, the AR(p) model has the nice property that, if you already know the correct value of p, fitting the AR(p) model can be done with an ordinary least squares regression.

randalolson.com: What makes for a stable marriage? | Randal S. Olson

randalolson.com: What makes for a stable marriage? | Randal S. Olson
How many people attended the wedding If you’re following the above guidelines, you’ve been dating your partner at least 3 years before getting engaged, making a combined $125k salary, go to church together regularly, and don’t worry about your partner’s wealth nor looks. The Big Day is coming up and you’re set to be happily married for life, right? Wrong! Crazy enough, your wedding ceremony has a huge impact on the long-term stability of your marriage. Perhaps the biggest factor is how many people attend your wedding: Couples who elope are 12.5x more likely to end up divorced than couples who get married at a wedding with 200+ people. Clearly, this shows us that having a large group of family and friends who support the marriage is critically important to long-term marital stability.

norvig.com: English Letter Frequency Counts: Mayzner Revisited or ETAOIN SRHLDCU

norvig.com: English Letter Frequency Counts: Mayzner Revisited or ETAOIN SRHLDCU
My distillation of the Google books data gives us 97,565 distinct words, which were mentioned 743,842,922,321 times (37 million times more than in Mayzner’s 20,000-mention collection). Each distinct word is called a “type” and each mention is called a “token.” To no surprise, the most common word is “the”. Here are the top 50 words, with their counts (in billions of mentions) and their overall percentage (looking like a Zipf distribution):

Green Tea Press: Free Computer Science Books

Green Tea Press: Free Computer Science Books
Most textbook authors sit down with the goal writing the bible of their field. Since it is meant to be authoritative, they usually stick to well-established ideas and avoid opinion and controversy. For most professors, the cardinal virtue is course materials; they want a course-in-a-box. And judging by the email I get, what they really want is solutions to the exercises. Unfortunately, price is usually not an issue. The result is an expensive 1000-page book with no personality. For students, these virtues are irrelevant because textbooks are unreadable and, usually, unread. Here’s what happens. The professor chooses a 1000-page book and assigns students to read 50 pages a week. They can’t, and they don’t, so the professor spends class time explaining what the students couldn’t read. Before long, the students learn that they shouldn’t even try. The result is a 1000-page doorstop. What’s the solution? Easy, it’s the opposite of everything I just said. Authors need to write books stud

Clicky.com: Web Analytics in Real Time

Clicky.com: Web Analytics in Real Time
All data in Clicky is up-to-the-minute real time. Not just a few reports. Everything. Clicky lets you see every visitor and every action they take on your web site, with the option to attach custom data to visitors, such as usernames or email addresses. Analyze each visitor individually and see their full history. In addition to standard per-page heatmaps, Clicky also lets you view heatmaps for individual visitor sessions, including segmentation. For example, you can view heatmaps only for visitors who completed a specific goal. Heatmap data is real time.

people.engr.ncsu.edu: Is Programming Knowledge Related To Age?

people.engr.ncsu.edu: Is Programming Knowledge Related To Age?
Becoming an expert at programming is thought to take an estimated 10,000 hours of deliberate practice. But what happens after that? Do programming experts continue to develop, do they plateau, or is there a decline at some point? A diversity of opinion exists on this matter, but many seem to think that aging brings a decline in adoption and absorption of new programming knowledge. We develop several research questions on this theme, and draw on data from StackOverflow to address these questions. The goal of this research is to support career planning and staff development for programmers by identifying age-related trends in StackOverflow data. We observe that programmer reputation scores increase relative to age well into the 50’s, that programmers in their 30’s tend to focus on fewer areas relative to those younger or older in age, and that there is not a strong correlation between age and scores in specific knowledge areas.

piwik.org: Free Web Analytics Software – Analytics

piwik.org: Free Web Analytics Software – Analytics

Piwik is an open analytics platform currently used by individuals, companies and governments all over the world. With Piwik, your data will always be yours.

Get to know more about your users and their behaviour on your website – where they came from (referrers), which pages are most popular, how often they visit and which marketing campaigns have been successful.

Whether you are an individual blogger, a small business, or a large corporation, Piwik helps you gain valuable insights to help your business or readership grow.

Piwik will always respect your and your users’ privacy, while giving you full control of your data.