TESTING LATEST UPDATE
COMPREHENSIVE SCRIPT 2026 COMPLETE
QUESTIONS AND SOLUTIONS GRADED A+
⩥ Power analysis. Answer: how sample sizes are calculated
⩥ Power. Answer: The ability to find a difference or an association when
one actually exists
- inverse of Type II error and is calculated as 1- B.
- if power is high, it strengthens meaning of finding
- if power is low, researchers need to address this issue in the discussion
of limitations and implications of the study findings.
⩥ Type one error. Answer: the error made when a researcher incorrectly
rejects the null hypothesis, when he or she concludes there is a
significant relationship but there really is not
⩥ Degrees of freedom (df). Answer: number values that are "free to be
unknown"
,⩥ Type two error. Answer: the error made when a researcher accepts the
null incorrectly, missing an association that is really there (sometimes
called a power error because the researcher may not have enough power
to find an association that really exits).
- is the probability of retaining the null hypo. when it is in fact false.
⩥ Null hypothesis. Answer: means that there is no
relationship/association or difference between or amongst the variables
of interest
⩥ Chapter 8 CHI_SQUARE. Answer:
⩥ Chi-square (x2). Answer: a test used wit independent samples of
nominal -or ordinal- level data
⩥ Statistical Concepts. Answer: mathematical calculations we do with
#'s...like bp's, 02 etc. BUT..
anxiety, cigarette smoking cession have to be converted to run
mathematical calculations that's why researchers create questionnaires
with scales, that they then apply numbers to so they can measure those
things.
ex: pain is measured by mathematical #'s and scale is used on a 0-10
scale, that way they can be converted to #'s then analyzed statistically.
This lecture will introduce:
, Two basic mathematical principles upon which all statics are based.
⩥ Probability Theory. Answer: PROBABILITY:
Can predict future events
⩥ Example of Probability
p= 0.1=10% 1 of 10 break
p=0.95=95% 95 of 100 break. Answer: Drinking glass example
⩥ Why isn't it 100% Probability
in drinking glass example.. Answer: we didn't measure any of other
variables to see why glasses didn't break, that's why it's not 100%
-could have purchased at different places, concrete could have been
warmer or temperature of glass could have mattered.
⩥ Probability Example. Answer: What will probability of your grade be
if you take a test on something you know nothing about...like astro-
physics. ANSWER IS...... (see next slide)
⩥ Probability Answer to Astro-physics test of which you know nothing
is...