## Statistics: rarefaction curve

Self-tutoring about statistics: the tutor mentions rarefaction. I’ve seen the terms rarefy, rarefied, rarefaction, etc, but never knew what they meant. Today I decided to change that, but it was like opening an overfilled closet where everything jumps out at …

## Statistics: base rate fallacy, part 2: belief vs disbelief

Tutoring statistics, so many inroads are available. The tutor continues about the base rate fallacy. Continuing from my post yesterday, I’ll explore a connection to it: believing what you see, vs not. The base rate fallacy means that people believe …

## Statistics: base rate fallacy, part 1: false-positive paradox

Tutoring statistics, you encounter day-to-day ideas. The tutor mentions the false-positive paradox. false-positive paradox: In a population where condition A is extremely uncommon, most tests for it that yield “positive” may likely be false. The false-positive paradox is easy to …

## Statistics: the 68-95-99 rule

Tutoring statistics, rules of thumb can be key. The tutor mentions a real-life application of the 68-95-99 rule. With hot, dry weather comes also the job of irrigation, for those who choose to do so. My wife wants a nice …

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## Statistics: how often can something “better” be expected to perform better?

Tutoring statistics, you might imagine everyday situations. The tutor brings up one. Let’s imagine we have two mile runners. Runner 1, called R1, has mean time 4:45, with standard deviation 10s; R2 has mean time 5:00 with standard deviation 12s. …

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Tutoring stats, you deal with p-values. The tutor shows an Excel connection. In my posts here and here I mention p-values. Example: Using Excel, get a two-tailed p-value for z=2.4 Solution: Using symmetry, it’s best to get the cumulative z-probability …

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## Statistics: Ten facts about the chi-square distribution

Tutoring statistics, distributions are of constant interest. The tutor brings up ten points about the chi-square distribution. The chi-square distribution may not be discussed much in a first-level stats course. It’s used to estimate or evaluate variance, rather than central …

## Statistics: an assumption of the linear regression model

Tutoring statistics, linear regression is perennial. The tutor mentions an assumption it includes. When appropriate, linear regression models data by the equation y = a + bx + e, e being an error term due to variability. An inherent assumption …

## Estimation of expected value: why sample mean is usually preferred over median

Tutoring statistics, mean is used more than median. The tutor points out a reason why. In my post from November 30, 2014, I write about why the median might be preferred to the mean in some cases. For instance, the …

## Statistics: When can you use the normal approximation to the binomial distribution?

Tutoring statistics, rules of usage are key. The tutor shares one about when the normal approximation to the binomial distribution can be used. The binomial distribution imagines a series of n trials, each with probability p of success and q=(1-p) …