u/rex5249

maybe you could edit your post and add this link: of a shooting in a bar in Nevada that was stopped by somebody carrying a concealed weapon. I live in NV and heard about it through the grapevine, then found the story (also note that you can carry a gun in a bar if you have a concealed weapon permit, and most of NV [except Las Vegas area] is open-carry, meaning that any non-convict can carry a gun in a holster): http://www.freerepublic.com/focus/f-chat/2021752/posts

If possible, note how many opportunities for cooperation existed for each person!!! The person with the lower count could have conceivably responded to 100% of the opportunities for cooperation and the other person responded with only 10%.

As for using a particular distribution for glm, I would want to see a larger sample (from similar research??) to get an idea if the chosen distribution is even remotely appropriate. If you can count the opportunities for cooperation, then you might have a different approach.

See if you can find similar studies that others have done and see what methods they used.

Ultimately you should determine how the state will grade the papers and teach that method. I don't know that answer.

Construction of box-and-whisker plots is an art. There are versions based on standard deviation, versions based on quartiles, and different options on how long to make the whiskers.

The R program for statistics has 9 different methods for calculating quantiles (percentiles/quartiles...). The different methods produce different results when dealing with duplicate values (at the quartile cutoff point) and interpolating between values when needed.

See http://www.jstor.org/stable/2684934

If you read the original Pew report, you'll get an entirely different view:

http://www.people-press.org/files/legacy-pdf/10-15-12%20Global%20Warming%20Release.pdf

on page 3: only 30% of Republicans say that scientists agree that the cause of warming is human activity and only 19% of Republicans say that the problem is very serious. Page 4 is a bit more promising: almost half of younger Republicans think that human activity is causing global warming.

Page 5: only 18% of Romney voters think that the earth is warming due to human activity---somewhere in there is some math that says that only the dumbest people who call themselves Republicans bother to vote.

I lived near the Nevada Test Site. You can start getting an idea of the incidence of leukemia near nuclear test sites here:

https://en.wikipedia.org/wiki/Nevada_National_Security_Site#Cancer_and_test_site

http://www.mendeley.com/research/leukemia-utah-radioactive-fallout-nevada-test-site-case-control-study/

Keep in mind that the effects of radiation from the tests were influenced by wind direction. There was a test farm on the Nevada Test Site with dairy cows, but as far as I know the milk was not put into the food chain. I think there were effects on the food chain from the Chernobyl incident, but I don't have the references right now.

You might also want to look for information about leukemia near uranium mines: http://www.wise-uranium.org/uhr.html

My first advice would be to talk to a psychologist. There could be causes of your anxiety that you are not addressing with your current practice or that cannot be addressed with meditation.

If you want to use meditation, one idea would be to recognize that your desire for a given goal (being free of one type of anxiety or another) is itself related to your experience of anxiety. Attempt to see your anxiety as an emotion, observe it, and focus on the physical sensation of the emotion instead of focusing on comparing your current state to a goal state.

Also note that if you become very anxious, it can take several hours for the stress hormones to metabolize. This means that it is unlikely to go from a state of high anxiety to tranquility in 15 minutes. What you can do in the short term is reduce the degree to which your thoughts are churning on a stress-inducing subject.

I searched for "meditation" on youtube and found 394,000 hits. You might want to ask yourself if something is missing from what is currently online and try to provide that.

I think practicing with a group is essential to developing a good personal practice. I previously looked for an online group (like a video chat room) dedicated to live meditation, perhaps with at least two rooms (or two dedicated time slots) that vary according to experience -- one for new meditations that has short meditations followed by Q&A, and at least one other that has longer meditations followed by Q&A. Different "experts" from various backgrounds could volunteer to lead each session.

A good format for such a thing might be to have at least some sessions that are designed to operate with only minimal leadership. I was in a group where we meditated for 40 minutes then we had a conversation that was confined to the practice of meditation (not to random people off the street talking about what they read in a Buddhism book--but there could be a room or session for that). The general guideline was to (1) keep questions and answers focused on the act of meditation, and (2) place great emphasis on each member speaking from experience, (3) avoid talking about what you read in a book. For an online group, you might add: (4) no selling any product or services. It worked well with only occasional guidance from a leader. You could add dharma talks separately, but there are already hundreds of people posting dharma talks.

Maybe you entered the data incorrectly. Each row of data should contains information about one team in one year (you could enter wins and losses or maybe just the percent). Also be sure that the data is numeric and not imported as strings--try adding 1 to each value to ensure that the computer can do it properly.

The article mentions confidence intervals, but I didn't notice any presentation of those intervals when I scanned the article. This would be a "confidence interval on Pearson r," which uses "Fisher's r to z transformation." You can get a rough idea of the procedure here:

http://www.onlinestatbook.com/2/estimation/correlation_ci.html

The confidence interval will tell you that there is a 95% chance that the real correlation is within two numbers. If the interval spans across zero, then it is possible that there is really no correlation between the variables.

McDonald's is always looking for competent people to work the register.

As an investment. When economic riots start, their won't be enough time to make enough bullets to shoot all the unarmed protesters. Cops will pay top dollar, and the SSA will be sitting on a gold mine!

You would need two water-delivery systems to send unpurified pond water or other such stuff.

If it really bothers you, you can capture your own grey water in buckets and pour it in the toilette. Capturing water from the shower should "doo" the trick.

yes, and it's also too big.

It's generally a bad idea to start with a statistical technique and try to apply it to unfamiliar data. Stock market data is also a bad choice. Forget the stock market---if a novice could predict the stock market after a few weeks of study everybody would be doing it.

I looked at the table of contents of that book. I have read some of those articles, and I would say that the book would be a good reference for grad students but you won't have time to really understand much of those topics before graduation. If you are at a university (that has a graduate school), you probably already have access to many of those articles through online databases. Print that table of contents and talk to your librarian.

A more efficient use of time would be to find several books including a "how to" book that matches theory to the computer program that you use. Books will be much easier to understand--articles about GLM are often written for people who already understand the technique. If you are a stats major, John Fox's book on Applied Regression has a chapter on GLM that is difficult but concise. Some of the homework problems are difficult, but it is a good book. You should also look for an easier book or two to complete your collection--some books don't say much more that to indicate which buttons to push in the computer program, but sometimes they help overcome obstacles.

One thing that might be useful is to build some programs to estimate the power of GLM analyses. r/stats has plenty of examples of people who collected data then realized that they didn't have enough power to answer their research question. Depending on the analysis, you might find equations to calculate power, or use bootstrap. Then estimate power to do some simple experiment look pulling numbered ping pong balls from a bag using the predetermined sample size. Bootstrap power estimates sometimes take weeks to calculate, so don't plan too big.

With the Nyquist program (http://nyquist.sourceforge.net/), you can use the yin function to detect frequency, but R is easier for me to program.

1) Have everybody flip a coin 10 times, then predict the number of heads on 10 more flips. Shoot the ones who say something other than 5.

2) Have people record the results of rolling 1 die, then 2 dice, then 10 dice. Create histograms or frequency tables for each sample size and talk about standard error of the mean.

3) Ask students to make a frequency table of shirt-color, then review the answers and discuss the need for clear, operational definitions and good measurement (is a green and red striped shirt green or red?)

4) Bring a pachinko machine to class and discuss the normal distribution (OK, that's expensive). Here is an alternative that I thought of: build a pachinko machine by putting skinny bolts into a pegboard (with the nut used to hold the bolt in place) then lean the board at 45 degrees and drop marbles down the top. You would have to capture that marbles in little slots at the bottom, then count how many fall into each slot at the bottom.

5) Throw balls of paper into the trash can from 2 distances and do a t-test. Record the number of success after 10 throws (this is not normally distributed, but close enough for an intro class). Maybe you could also talk about skew.

6) The birthday match things is interesting (counting the number of matching birthdays in the classroom), but I'm a fan of privacy and would prefer to not do this.

7) For probability, bring two bags of colored poker chips with different proportions of red and black chips. Have people draw 20 chips from each bag and build a chi-square table (maybe walk around the class and have people choose 2 from each bag, but be sure to have somebody write the results on the board as you go or people will forget which chips came from which bag.

8) You can discuss simulations that use random number generators, but some people will not be convinced or will fall asleep. If you take this route, write your own programs so that you know exactly what the program is doing and so that you don't have to wait for a slow online demonstration. If done properly, I think that simulation exercises can help people to understand things like t-tests, chi-square tables or standard error of the mean.

*) Avoid questions about playing cards--some students from India and other countries have religious objections to gambling and they are not familiar with playing cards. One classroom exercise would not prepare such a student for a question about face cards on a quiz. Dice are easy enough for anybody to learn.

*) Don't ask students about their weight or height or P!@#S length to demonstrate a normal distribution. Some students are hyper sensitive about such things.

p.s.: consider the degree to which your post says the following:

1) You feel bad or empty. 2) You notice that your job is mostly nonstatistics work 3) You assume that returning to school or doing more statistics work or taking a vacation will correct the bad or empty feeling. 4) Evidence to support the conclusion in #3 is: {} <<<<that's the empty set!

Consider that rethinking your perception of your situation might help---hence my first post.

I left the corporate world about 7 years ago, but there is no way that I would try such a thing in today's economy.

Funding for higher education is on the chopping block meaning that it might be more difficult to fund school or find an academic job when you are done. In the event that you can get into a PhD program for stats and in the event that you graduate, it is probably a poor financial decision given the cost of school (including opportunity cost) and the possibility that any increase in pay later will not cover the sacrifice.

Here are some alternatives:

1) Take a class in meditation. Perhaps try insight meditation or vipassana or something that does not involve chanting. Don't do it online--go to a class and practice with a group, then continue to practice with the group after the class is over. If you are lucky enough to find a good teacher, you might discover that meditation helps you to perceive your emotional situation differently than you currently do (and thereby offer yourself an alternative to your current reaction to your emotional state).

2) Pay $100 or so for a business license, spend a few bucks on a suite, and open a consulting business (in your spare time). Small businesses will have no idea what you are talking about, but if you sound smart and tell people that you can save them money, you might get some work. Do volunteer gigs for notable nonprofits in your city or for local government, then put that on your resume. Who knows where that could lead? When you put yourself in a position where you have to produce something valuable or look like a fool, you won't have time to be bored.

3) You won't like this one, but talk to a psychologist. When you consider the lost wages during school and the risk that you won't finish the program or that you will finish but find yourself in a different job that you hate more than this one, the cost of talking to a shrink for a few months is mighty small.

I haven't done a split-plot, but I'm wondering about the time variable. How many time periods are there for each person, and how consistent were the time intervals?

I'm guessing that the time between measurements is not consistent and that is why somebody suggested split-plot. If your time intervals are not constant but there is a general trend toward decreasing pain, then your ANOVA will find a difference, but what question would this answer?

Have you tried running a regular time series analysis? Code the time variable so that it is on some kind of consistent scale---maybe with t=0 for the day of operation and then the number of days or months to each pain test (always counting time from starting from the operation date). Use "time" as a regular fixed effects variable to predict pain (this is just a regular numeric variable in a regression). Code pain into TWO dummy variables: one will be 1 if the grade is 2, else zero. another will be 1 if grade was 3, else zero. Grade 1 is the baseline and doesn't get a dummy variable (if the other two are zero, then you know the grade was 1).

If you have only 2-3 time samples for each person and there is great inconsistency in time, then you might not be able to do much other than a rough regression. If the time period were really consistent across subjects and you only had 2-3 samples, you could add it as a grouping variable to capture any nonlinear trend (although I wouldn't do that). If you have abundant time periods for each person, then time series becomes a good option.

Do you think that glorifying U.S. soldiers WWII leads young people to associate the military with something noble thereby helping today's soldiers to mentally justify killing people in the Mid-East for oil?

"Surface air temperature" would the the complete phrase. This would be in contrast to atmospheric (high altitude) readings or ground temperatures.

I had seen something a couple weeks ago about "ground temperature" to refer to the temperature of the dirt in Death Valley, CA (201 F): http://www.nps.gov/deva/naturescience/weather-and-climate.htm

Your thermometer is in the sun or it is broken. There is an official way to measure surface temperature--it's something like 6 feet off the ground under some shade or in one of these enclosures: https://en.wikipedia.org/wiki/Stevenson_screen

I have a few additions to what has been posted so far. I don't know exactly what you do, but you should plan on studying stats for a long time and not expect to be finished by reading one text book. You might start with an introductory book or course, then try a book on multivariate stats (Tabachnick and Fidell is good), then study specific methods that you encounter (like SEM, factor analysis, or whatever) to go into more detail. Note that textbooks don't always cover all the details. They might not tell you exactly how to test the statistical assumptions.

If you don't seem to benefit from reading the text book, try taking a class at community college or online.

If you can learn on your own, get an introductory stats book by buying a slightly out of date edition from eBay (they are much cheaper than the latest version).