stdevp( ) appears to be mislabeled

[Mike Elzinga]

(06-05-2016 10:34 PM)Wes Loewer Wrote:  

(06-05-2016 09:57 PM)Mike Elzinga Wrote:  I have a TI-89 Titanium; and I just checked.
The TI-89 has stdDev (division by N-1) and stDevPop (division by N).

Interesting. Apparently stDevPop() was added to the 89 in OS 3.10, but was not present in 2.09. (The function could be added by installing the Stats App.)

And just to clarify in case anybody's wondering, on the 84+, you can calculate the population standard deviation using 1-Var Stats, but there's not a population standard deviation "function" that corresponds to the sample standard deviation function, stdDev().

I have suggested to students to think of these mathematical functions as divided into two major categories;

(1) a category of functions that are used to describe and characterize a population. when we can do so, by calculating various population parameters such as the mean, standard deviation, median, quartiles, minimum, maximum, kurtosis, and skewness, etc.;

and

(2) another set of similar functions used to calculate sample statistics that are estimates of those parameters and also produce the probabilities that they wrong in their estimates.

The behaviors of these latter functions are that they deviate from their estimate of population parameters less and less as the sample sizes get larger and larger. The distributions followed by repeated samples of a given size allow us to come up with those probabilities that we are wrong.

We typically start with the z test and move to the Student's t-test; and from there the pattern of estimation remains pretty much based on the behaviors with sample size that have been observed with these simpler of the statistical inferences from the sample to the population.

This is where the naming of functions - or at the very least, the descriptions of them in the help menus - becomes a matter of good pedagogical practice in getting students to understand what they are doing when using a statistic to get at a population parameter; or even further in why the sample sizes can quantitatively set the boundaries of certainty or uncertainty in a particular measurement.