Notes for September 29 and October 1

Here are links to posts about how to get average and both standard deviations on the TI-30XIIs.

Here is a link to a post about t-scores and their use in confidence intervals.

Here is a link to the posts about Confidence of Victory.

A list of what the major things that can go wrong with samples.

Too small a sample size. A very small sample will have huge confidence intervals for the values of proportions for categorical variables, which should be a red flag for anyone reading it. But often, people only mention n and the confidence intervals as afterthoughts and many papers have been published and quoted in much larger publication before anyone notices how small the samples were.

Convenience sampling: Our class could be considered a sample of students at Laney, but is it representative? It's convenient for me to get information from the students, but groups of students who would be ignored include:

1. Students whose majors do not require statistics
2. Students who primarily take night classes or distance learning classes
3. Students who primarily take Monday and Wednesday classes

It's not inevitable that excluding these groups would change the proportions of males and females, for example, but a convenience sample is always suspect.

Self-selection. Internet polls on websites might ask you about politics or sports or entertainment. You are under no compulsion to answer the questions and you do so only because the topic interests you. Instead of being convenient for the researcher, self selection polls are convenient for the responders. Almost every such poll will have a disclaimer stating "not a scientific poll" and the numbers aren't a good place to start using statistical methods to find out about the underlying population.

Leading questions. In polling data for opinions, leading questions can create bias.

Under-sampling and oversampling of demographic groups. I have been following polls for several elections now and in nearly every poll, someone will complain that some group is under-represented.  Too many conservatives or too many liberals, too many men or too many women, not enough people from outside of major cities or too many from outside major cities, some age group is under or over represented.

No sample is completely perfect, but honest sampling companies do work at using acceptable methods.