Sentences with phrase «standard age error»

So you fuzz your data into the error ranges, e.g. your datum says 1500AD with standard age error of 150 years, so you write 1000 records into the range 1350AD - 1650AD — taa daa, your data now includes the standard error.

Not exact matches

Mean and standard errors of monthly weight gain after adjusting for maternal age; race / ethnicity; education; household income; marital status; parity; postpartum Special Supplemental Nutrition Program for Women, Infants, and Children program participation; prepregnancy body mass index (calculated as weight in kilograms divided by height in meters squared); infant sex; gestational age; birth weight; age at solid food introduction; and sweet drinks consumption.

By taking the age of patients» blood cells into account, the researchers» model, when tested in more than 200 diabetic patients, reduced the error rate from one in three patients with the standard blood test to an error rate of one in 10.

Fig. 2 Median age (and standard error) at reported diagnosis for genetic conditions and vehicular injury for intact (dark bars) and neutered (light bars) females (a) and males (b).

The distribution for the measurement of carbon - 14 age has (we're assuming) the same standard deviation for every calendar year, so it's always that case that we get some particular carbon - 14 measurement that was «unlikely», since any particular value for the measurement error is unlikely.

take a horizontal ruler on fig1 and put it half a standard deviation of the measurement error (50y) higher up than the C14 age mean (the maximum of the red curve).

P (Obs calendar - age = y) does not change much when y changes by a small amount, small enough that the carbon - 14 age changes by much less than the standard deviation of the measurement error.

This integral is over the same region for any hypothesized calendar age, and therefore can be ignored when the amount of rounding is small compared to the standard deviation of the error.

If the measurement for carbon - 14 age has Gaussian error with standard deviation 100 (as seems about right for Nic's Fig. 2), and the measurement is rounded to one decimal place, and the calibration curve maps calendar age 750 to carbon - 14 age 1000, then the probability of the observation being 1000.0 given that the calendar age is 750 is 0.1 (for one decimal place) times the probability density at 1000 of a Gaussian distribution with mean 1000 and standard deviation 100, which works out to 0.0004.

The age profile is very similar to that I've already posted only with narrower standard errors.

As well, since different numbers of trees contribute at different ages, both the raw averages and the standardized averages (by subtracting the number one and then dividing by the standard error) were calculated.

The volatility is just a reflection of the fact that there aren't many such trees — this is reflected in the width of the standard errors through this portion of the age curve.

Standard errors blow out massively from that point on and the point estimate for age ~ 400 is (approximately) zero in any case.

How easy is it to report standard errors around your LOESS age function?

Suppose I generate a graph of the age and year coefficients with standard error bands (it's quickest if I do this in Excel of all things)-- how do I post it here?

Then, we conducted sensitivity analysis comparing the mean scale scores across age and gender among the complete cases, all of the available cases, and the imputed cases (coefficients and standard errors from 5 data sets were adjusted for the variability between imputations according to Rubin's rule).