Welcome to Really Simple Statistics (RSS). There are lots of places online where you can ponder over the minute details of complicated equations but very few places that make statistics understandable to everyone. I won’t explain exceptions to the rule or special cases here. Let’s just get comfortable with the fundamentals.
What are tails?
No, not these tails.
The tails in statistics refer to the predictions we make about our research results and how we want to hedge our bets.
One tailed tests
One tailed tests are what you use when you have a specific guess. Men are taller than women. Women like chocolate more than men like chocolate. Roses smell nicer than tulips. It’s like putting all your eggs in one basket. Take a guess and hold yourself to it.
Ideally, this is what you should be aiming for. You should have a prediction about what is going to happen before you conduct your research. You should do your homework and not just willy nilly see ‘what comes up significant.’
One tailed tests are advantageous because they give you a better chance of generating differences that turn out to be statistically significant, as long as, of course, your prediction turned out to be right.
Two tailed tests
Two tailed tests are used when you can’t make a guess. Will men or women eat more bread? Is basketball or soccer more fun? Do people spend more on coffee or on hot chocolate? In this case, you’re putting splitting your eggs between two baskets – maybe men but maybe women, maybe basketball but maybe soccer.
jdurham from morguefile
In reality, most of what we do in market research is based on two tailed tests. We don’t spend the time to develop specific hypotheses ahead of time. We wait to get the datatables and then search through hundreds of pages looking for whatever happens to be significant.
And that’s it! Really Simple Statistics!
- Study Asks, Can You Trust Google’s Personalized Search Results? (searchengineland.com)
- Pie Charts – Our Evil Friend
- Cronbach’s Alpha, My Favourite Statistic
- Why Do I Always Screen Out of Surveys
- Qualitative Research on a Quantitative Scale?