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One Sample Hypothesis testing
tests an assumption about the
population based on the sample statistic, giving us the following null
and alternative hypothesis formats:
Two sample Hypothesis testing
compares the population parameter of
two sets of data, giving us the following null and alternative hypothesis
formats, with d0 (or µD, dµ, or pD, dp from other sources) being the
assumed difference of the said population parameters.
Independent testing
If sample set A has no relation to sample set B
• If the entities in sample set A are different from the entities of
sample set B
• If sample set A is not an effect of sample set B, vice versa
Dependent Testing (Matched Pairs)
If sample set A has immediate relation to sample set B
• If the entities in sample Set A are the same entities in sample
set B
• If sample set A is an effect of sample set B, vice versa
• If the sample sets are paired
MULTIPLE
CORRELATION
yields the maximum degree of linear
relationship that can be obtained between two or more independent
variables and a single dependent variable.
INPUT (INDEPENDENT VARIABLES)
Materials, information, labor, energy, conditions
PROCESS (SYSTEM)
Machine, chemical reaction, human activity,
program
OUTPUT (DEPENDENT VARIABLE)
Products, results, possible outcomes