[New York Times, Nov. 13, 01--report on the finding of the first anthrax case in New York City:  The test that was first used was new; they hadn't had time to confirm the results by the usual method of growing a culture.]
Dr. Koplan, director of the Centers for Disease Control and Prevention, on the phone with Mayor Giuliani:
    "Are you sure it's anthrax?" the mayor asked.
    "Well, we have a high degree of probability," Dr. Koplan replied.
    "No, no, no, don't give me that stuff," was the mayor's rejoinder. "Is it anthrax or is it not?'
    "Yes," Dr. Koplan said.
    "Fine, that's all I needed to hear," Mr. Giuliani said.

"Significance testing" vs. "Hypothesis testing"-- two different approaches that blur...
Both start with null and alternative hypotheses.  You want to show the alternative is true.

Significance testing:  Calculate P-value (or closest alpha), describe how unusual your result is if H0 is true.
Let the audience for your work decide if they believe in the alternative hypothesis or not.  (Scientist's approach.)
   Language: "strong evidence for Ha, against H0 or not strong...

Hypothesis testing:  Make a decision  between H0 and Ha (often associated with predetermined fixed alpha level)
We need to do something.
    Language:  "Accept Ha, reject H0" if P-value smaller than alpha.
        What if we can't reject H0?  Do we accept H0? Safer:  "fail to reject H0"
     H0 "Innocent"                 "Guilty" Ha
                     \ "Not Proven" /         but defendant goes free...

If we make a decision we run the risk of error:
Type I error Accepting alternative Ha when null H0 is true (probability = alpha)  Test designed to focus on this one.
Type II error, Accepting null H0 when alternative  Ha is true (probability = beta, depends on what exact parameter value in  Ha is true)  Can't make this one if we refuse to commit, but
A small Type II error means the "power" of the test to detect  the alternative hypothesis when it's true-- is high.
(Sec. 6.4, optional, takes this further)

Larger sample size gives stronger power to detect a true alternative.


Sievers home  Math151-Sp02/Sig_vs_hypoth.htm  4/22/02
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