search for: underreported

On 11/8/2014 6:54 AM, thomas schorpp wrote: > Dear Ted, > > Am 07.11.2014 um 17:47 schrieb Ted Mittelstaedt: >> On 11/3/2014 9:25 PM, thomas schorpp wrote: >>> Hi Ted, >>> >>> Am 04.11.2014 um 04:12 schrieb Ted Mittelstaedt: >>>> >>> >>>> Note that since the UPS relies on the voltage from the battery pack to

hi. i've looked for (and not found) an assert() function. needing one, i created the following (from stop()). i'm posting it in case 1) someone sees a problem with this; and 2) someone else has a need. cheers, Greg ---- ## an assert mechanism... assert <- function (shouldbe, ...) { if (!shouldbe) { .Internal(stop(as.logical(TRUE),

I came across this one: http://www.nysun.com/article/32787 which says that the violent death rate in Iraq (which presumably includes violent deaths from the war) is lower than the violent death rate in major American cities. Does anyone have any insights from statistics on how to interpret this?

Dear Ted, Am 07.11.2014 um 17:47 schrieb Ted Mittelstaedt: > On 11/3/2014 9:25 PM, thomas schorpp wrote: >> Hi Ted, >> >> Am 04.11.2014 um 04:12 schrieb Ted Mittelstaedt: >>> >> >>> Note that since the UPS relies on the voltage from the battery pack to >>> determine state of charge, it is quite useful to add in the battery pack >>>

Curses, my laptop is hallucinating again. Hope I can get through this. So we're talking about correlations between binary variables. Suppose we have two 0-1-valued variables, x and y. Let A <- sum(x*y) # number of cases where x and y are both 1. Let B <- sum(x)-A # number of cases where x is 1 and y is 0 Let C <- sum(y)-A # number of cases where y is 1 and x is 0 Let D <- sum(!x

Hi Richard, Nice to know you had similar experience. Yes, your understanding is right. all correlations are negative after removing double-zero rows. It is consistent with a heatmap we generated. 1 is for a cancer patient with a specific mutation. 0 is no mutation for the same mutation type in a patient. a pair of mutation type (two different mutations) are exclusive for most of patients in

On 11/3/2014 9:25 PM, thomas schorpp wrote: > Hi Ted, > > Am 04.11.2014 um 04:12 schrieb Ted Mittelstaedt: >> > >> Note that since the UPS relies on the voltage from the battery pack to >> determine state of charge, it is quite useful to add in the battery pack >> voltage to the logs as such: >> >> --- upslog.c.orig 2012-07-31 10:38:58.000000000

The Wine development release 1.1.9 is now available. What's new in this release (see below for details): - A large number of regression test fixes. - Performance improvements in memory management. - Improved POP3 support in inetcomm. - Initial implementation of the XInput DLL. - Various bug fixes. The source is available from the following locations:

Your expanded explanation helps clarify your intent. Herewith some comments. Of course, feel free to ignore and not respond. And, as always, my apologies if I have failed to comprehend your intent. 1. I would avoid any notion of "statistical significance" like the plague. This is a purely exploratory exercise. 2. My understanding is that you want to know the proportion of rows in a

HI Bert, Thank you for extra help!! Yes, exactly, your interpretation is perfectly correct and your R code is what I should look for. after generated all those negative values of correlation, I thought about the extremely small p values associated with those negative correlation, which is not meaningful as I truncated my data. When examining the exclusiveness of mutation pairs, what I first

Let's go back to the original posting. > > > >> in each column, less than 10% values are 1, most of them are 0; > > > > > > > >> so I want to remove a row with value of zero in both columns when calculate correlation between two columns. > > So we're talking about correlations between binary variables. Suppose we have two 0-1-valued