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 2d comment Statistical Significance If you are going to use the future perfect then perhaps you should move it out of the indicative, e.g. to "would have been rejected". You may also need to say the the "1%" represents the probability of erroneously rejecting the null hypothesis when it is in fact true, so "5%" involves that possibility and more. Jun19 comment What can we say about population mean from a sample size of 1? This seems to give confidence intervals covering the mean with probability about $95\%$ when $\sigma \approx | \mu | \gt 0$ but with much higher probabilities otherwise. If $\mu = 0$ then clearly the probability is $100\%$ as the confidence intervals always contain $0$. Jun14 awarded distributions Jun13 comment Percentile vs quantile vs quartile A deeper question is whether quantiles etc. are intervals or points. Jun12 comment Estimating median survival times from Kaplan-Meier plot inspection The data might show you that 16 out of 29 of the "mutation present" cases survived more than 4000 days (or whatever the numbers are), which is over 10 years. How would you work out the median from this? Jun11 comment Why is a symmetric distribution sufficient for the sample mean and variance to be uncorrelated? @Glen_b: I am well aware that zero correlation does not imply independence. In fact my two bullet points were designed to show this difference. By the way, looking at your deleted answer, I thought about the Cauchy example in your second half and so said "if they have a correlation", while your first half deals with the "only if" point which my mine did not (the question seemed confused about this); so you might think about undeleting it. Jun10 comment Correlation coefficient is very small Visually the relationship looks very weak on the right-hand side and if the regression line had been horizontal (something like $y=4$) I would not have been surprised May27 awarded Nice Answer May25 comment Standard Error of the ratio of Binomial variates $Y$ has a positive probability of being $0$ (so too does $X$) which is going to cause issues with $\frac {X-Y}{Y}$ May17 comment Clarify probability solution re. birthdays Remember that (in some countries at least) births on Saturday and Sunday are less common than on other days because doctors like not working at weekends. May17 comment Combine several days of time series into one Yes you can, though whether a simple linear regression would be meaningful is another matter (e.g. if you were measuring tiredness, there might be a cyclical pattern) May12 comment Poker and the Birthday Problem You can make order matter in your poker hands and have $\dfrac{52!}{47!}$ possible hands, i.e. $5!$ as many. You could easily adjust the rest of your analysis to fit this. But this option to choose whether to make order matter or not does not work so well with sampling with replacement especially if you want to use counting arguments. May10 comment Should I use A/B testing to find evidence that click-through rate has changed over four months? I would have thought the rate was $35/100$. You can certainly do something like what you are suggesting, but I would not all it A/B testing, which I would have thought meant showing different ads to different people in the same time period and comparing response rates May3 comment Stationarity after differencing If $\beta_1$ is a non-zero constant then $E[x_t]$ is increasing with $t$, so the original process is not constant in mean. May3 answered Stationarity after differencing May2 answered Training an SVM and performing cross validation Apr14 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? Apr10 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 $M$. Apr9 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. Apr8 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.