| Chi-square is a convenient measure of
| |
| | doesn't have a brain. It is merely an
|
| association between two factors when the
| |
| | algorithm of human frequencies, a
|
| factors are not quantitative. It
| |
| | mechanical process based on numbers
|
| indicates the degree to which the human
| |
| | regardless of what they represent. By
|
| frequencies in a cross-tab of the two
| |
| | itself, it never can take the place of a
|
| factors deviate from what they would be
| |
| | regression or correlation because it
|
| if there was no interrelation at all
| |
| | cannot describe the human frequencies,
|
| between the factors. The computed
| |
| | only gauge their statistical
|
| chi-square has a specific level of
| |
| | significance, entirely regardless of
|
| statistical significance looked up in a
| |
| | logic or sense.
|
| standard table.
| |
| | Chi-square is non-parametric. To describe
|
| Suppose we ask 300 testers to rate our
| |
| | a human frequency in numerical terms, we
|
| pretzels (A) and another brand's (B) both
| |
| | need numerical values-that is,
|
| in terms of overall preference and
| |
| | parameters. If we arbitrarily assign
|
| preference regarding human frequencies.
| |
| | value +1 to preference for A and -1 to
|
| By a convenient coincidence, the "crunch"
| |
| | preference for B, we can compute a
|
| preference divides exactly even, with 100
| |
| | correlation coefficient-r= +.246 for the
|
| preferring A, 100 preferring B, and 100
| |
| | original tabulation, and exactly half
|
| having no preference.
| |
| | that for the corrected distribution. The
|
| Clearly, there is a strong association
| |
| | parametric regression/correlation, unlike
|
| between the preference on "crunch" and
| |
| | chisquare, is affected by the way the
|
| overall human frequencies; chi-square is
| |
| | rows and columns are labeled because each
|
| 18.4, indicating a significance level of
| |
| | label has a specific value.
|
| 99%+ ... Wait a minute, there's the
| |
| | So chi-square is a very useful index when
|
| phone. What's that? I see... a
| |
| | we cannot assign values to human
|
| stub-labeling error, the last two lines
| |
| | frequencies, but it is very easy to
|
| got switched... Okay, thanks.
| |
| | misuse it; it doesn't have a brain, so
|
| So let's see, now we have:
| |
| | the analyst has to use his or her own
|
| That still looks like a strong
| |
| | brain to interpret it correctly.
|
| association for (A) but not for (B), so
| |
| | Though one doesn't necessarily need fancy
|
| we should have a lower chi-square, right?
| |
| | testing equipment to know how they feel
|
| No. Chi-square is still 18.4. As long as
| |
| | health-wise. Once the human body can
|
| the numbers stay the same, it doesn't
| |
| | absorb the right nutrition in the correct
|
| matter how they are labeled. Like the
| |
| | electrical patterns, health can't help
|
| Scarecrow in Wizard of Oz, chi-square
| |
| | but improve.
|
