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When is an answer not an answer?
When your beloved authors were studying research and statistics, around the time that Methuselah was celebrating his first birthday, we thought we knew the difference between hypothesis testing and hypothesis generating. With the former, you begin with a question, design a study to answer it, carry it out, and then do some statistical mumbo-jumbo on the data to determine if you have reasonable evidence to answer the question. With the latter, usually done after you’ve answered the main questions, you don’t have any preconceived idea of what’s going on, so you analyze anything that moves. We know that’s not really kosher, because the probability of finding something just by chance (a Type I error) increases astronomically as you do more tests.1 So, in the hypothesis generating phase, you don’t come to any conclusions; you just say, “That’s an interesting finding. Now we’ll have to do a real study to see if our observation holds up.”
Click on the PDF icon at the top of this introduction to read the full article.
When your beloved authors were studying research and statistics, around the time that Methuselah was celebrating his first birthday, we thought we knew the difference between hypothesis testing and hypothesis generating. With the former, you begin with a question, design a study to answer it, carry it out, and then do some statistical mumbo-jumbo on the data to determine if you have reasonable evidence to answer the question. With the latter, usually done after you’ve answered the main questions, you don’t have any preconceived idea of what’s going on, so you analyze anything that moves. We know that’s not really kosher, because the probability of finding something just by chance (a Type I error) increases astronomically as you do more tests.1 So, in the hypothesis generating phase, you don’t come to any conclusions; you just say, “That’s an interesting finding. Now we’ll have to do a real study to see if our observation holds up.”
Click on the PDF icon at the top of this introduction to read the full article.
When your beloved authors were studying research and statistics, around the time that Methuselah was celebrating his first birthday, we thought we knew the difference between hypothesis testing and hypothesis generating. With the former, you begin with a question, design a study to answer it, carry it out, and then do some statistical mumbo-jumbo on the data to determine if you have reasonable evidence to answer the question. With the latter, usually done after you’ve answered the main questions, you don’t have any preconceived idea of what’s going on, so you analyze anything that moves. We know that’s not really kosher, because the probability of finding something just by chance (a Type I error) increases astronomically as you do more tests.1 So, in the hypothesis generating phase, you don’t come to any conclusions; you just say, “That’s an interesting finding. Now we’ll have to do a real study to see if our observation holds up.”
Click on the PDF icon at the top of this introduction to read the full article.