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seen Apr 15 at 21:26

Apr
14
comment Why small values produce undulating densities when ploting logarithm of a loguniform prior (in R)?
If I try x <- 100^runif(1000000); plot(density(log(x))) then I get something which looks sensible between $0$ and about $4.6 \approx \log_e(100)$, so what did you run to get that oscillation?
Apr
10
comment Roll a 6-sided die until the total $\geq M$. Mean amount by which $M$ is exceeded?
I suspect that $M=300$ could be read as "very large $M$" as I believe that $M=301$ or $M=999$ would give almost exactly the same result. What I would do is find the distribution of the sum minus $M$.
Apr
9
comment Is there a name for this sort of plot? Is there any reason not to use it?
Difficult to find the $5$th percentile of $9$ observations. I think I would call what you are describing as a band chart: this is one (in fact two) looking at daily high and low temperature across the year in London.
Apr
8
comment Basic stats question - How to tell if my data distribution is symmetric
$-70,-63,-56,-49,-42,-35,-28,-21,-14,-7,0,1,4,9,16,25,36,49,64,81,100$ is deliberately not symmetric (uniform in the lower half but not in the upper half) and a box plot would put the median (equal to the mean) nearer the upper quartile than the lower quartile but also nearer the minimum than the maximum.
Apr
5
comment correlation between spelling ability and frequency of use of text messaging
You could start with a scatter plot to see what the results look like (though with a large sample you should be aware of overlapping points)
Mar
28
comment Closed form solution for t-stats and p-values in multiple regression
Excel has the TTEST function
Mar
28
comment Why do we need confidence intervals?
Yes. They might be equal by chance, but probably would not be.
Mar
28
comment Why do we need confidence intervals?
The expected value of the sample mean may be the population mean, but more often than not the sample mean will not be exactly equal to the population mean, and different samples are likely to have different sample means.
Mar
28
comment Why do we need confidence intervals?
It takes effort to look at every single account to get the exact answer with certainty, so taking a sample saves effort at the cost of some possible sampling error. The bigger the sample is, the smaller the sampling error is likely to be, but requires greater effort.
Mar
24
awarded  Constituent
Mar
20
comment The abundance of P values in absence of a hypothesis
That table is actually a good example of what happens with large sample sizes (even the small differences in average age appear to be significant, suggesting perhaps that average waistlines may widen with old age or perhaps that larger waists increase average life expectancy very slightly). But the $P$-values are not dominating the table and at best this is exploratory analysis which could provide hypotheses for future study (e.g. a longitudinal study seeing whether people's waists widen or whether they die). It also suggests some factors which might be worth controlling for in future work.
Mar
19
comment Why shouldn't the denominator of the covariance estimator be n-2 rather than n-1?
The denominator of your definition of sample variance is $n−1$ probably because this makes it an unbiased estimate of the population variance. The same is true of the sample covariance using the same denominator. But there are other definitions of sample statistics, with different denominators.
Mar
17
awarded  Caucus
Mar
9
awarded  Nice Answer
Feb
26
answered Why is the standard deviation defined using differences^2 instead of differences^4?
Feb
21
awarded  Excavator
Feb
21
comment When does replication reveal fraud?
"Statistics means never having to say you're certain"
Feb
21
revised When does replication reveal fraud?
numbering disrupeted by whitespace
Jan
28
awarded  Yearling
Jan
25
comment How to tell the probability of failure if there were no failures?
If there are few or no failures then $\Theta \sim U(0,0.1)$ will produce almost the same result as $\Theta \sim U(0,1)$ i.e. Beta$(1,1)$, and the latter is easier to handle