Having just looked at the Rational Zero Theorem, I realized we’ve never covered how to divide polynomials, which is used closely with that theorem. Here we’ll look at long division, and then, next time, at synthetic division, its efficient version.
A recent question reminded me that we have not yet covered the Rational Root Theorem (or Rational Zero Theorem), though it has been occasionally mentioned (e.g. here and here and here and here). It allows us to find any roots of a polynomial equation (that is, zeros of the polynomial) that might happen to be …
A recent question about the precise meaning of “difference” led me to some past discussions of the word.
A recent question led me to find a series of old questions, each answering it at a different level. All of them are worth presenting.
Last time, we looked at the Pigeonhole Principle, applying it to geometrical problems, largely about distances, gradually working from almost literal “balls and boxes” (“pigeons and pigeonholes”) to more abstract applications that are harder to see. Here, we will go beyond that, proving facts about sets.
A recent question involved the Pigeonhole Principle; we’ll start with an older question to introduce the idea, then the new question and a few old ones.
Last time, we saw a summary of the difference between population and sample standard deviation, along with other differences in formulas. Here we’ll look at two short answers about the reason for that difference, and then an extensive look at why it’s true. (I’ve taken extra time and space to work through details in order …
Sample Standard Deviation as an Unbiased Estimator Read More »
Last time we introduced standard deviation. Here we’ll look into why two formulas (namely, population and sample standard deviation) are different, and why several different formulas for either are equivalent. We’ll also discover how to update the standard deviation when a new value is added. In doing so, we’ll see some different perspectives than we …
Formulas for Standard Deviation: More Than Just One! Read More »
We’ve had a number of questions about “measures of dispersion”, such as standard deviation, which tell us how much data spreads out, as opposed to “measures of central tendency”, which tell us where the middle of the data is (as we discussed in Three Kinds of “Average” and Mean, Median, Mode: Which is Best?). Why …
A recent question illustrates well the different ways to solve problems in combinatorics. We’ll see an easy way, another easy way, and a … less suitable … way to solve a set of problems.