OUTLINE FOR CHAPTER
7 (Part 2)
(Note: Steps 1, 2,
are covered on the outline for the 1st half of Chapter 7)
- The Final 2 Steps (#5 & #3) of the Basic Hypothesis
- Step #5: The Criterion for Evaluating the Sample Evidence
- The primary question: "Are the sample data inconsistent with
what would likely occur if Ho
- Three possible outcomes when the numerical summary of the
sample data is compared against Ho's
pinpoint number . . . and what should be decided about Ho
- They're identical . . . and therefore Ho
obviously cannot be rejected
- A difference exists, but it's a "small" difference (i.e.,
small enough to be within the limits of expected sampling
error). . . and therefore it's not logical to reject Ho
- A difference exists, and it's a "big" difference (i.e.,
larger than what's likely to have been produced simply by
sampling error) . . . and thus Ho
should be rejected
- Two procedures for deciding whether an observed difference
(between the numerical summary of the sample data and Ho's
pinpoint number) should be considered "small" or "large"
- Compare the calculated value (obtained in Step #4) against
a tabled "critical value"
- Compare the data-based p-value (obtained in Step #4) against
the "level of significance"
- Step #3: Selecting the Level of Significance
- The level of significance as a "scientific cut-off point"
for deciding whether Ho should
- Popular levels of significance: .05 and .01 (and sometimes
.001) . . . with .05 used most often
- Different ways researchers talk about the level of significance:
alpha, a, p = .05, p< .05
- Type I & Type II errors (and how a
defines the former, influences the latter if a
- Two points of possible confusion regarding the level of
- Results That Are Highly Significant and Near Misses
- The kind of p
that causes a result to be "highly significant"
- Using different p-levels within the same study (even
though a constant a is used)
- The kind of p that causes a result to be a "near miss"
- Four alternative labels for an outcome that is a "near miss"
- The all-or-nothing approach to hypothesis testing
- A Few Cautions
- Two meanings of "alpha"
- The importance of Ho
- The ambiguity of the word "hypothesis"
- When p is reported to be equal to or less than zero
- The meaning of the term "significant"