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Test of significance
assess evidence for a claim about a population
statistical inference
provides methods for drawing conclusions about a population from sample data
upper critical value
the number Z_a/2 with probability p lying to its right under the standard Normal curve
Null Hypothesis (H0)
says that there is no effect or no change in the population
test for significance
is intended to access the evidence provided by data against a null hypothesis
alternative hypothesis
says that there is an effect or change in the population
one sided alternative
a parameter differs from its null value in a specific direction
two sided alternative
A parameter differs from its null value in either direction
P-value
is the probability that the test statistic will take a value at least as extreme as that actually provided
statistically significant
the p-value is as small or smaller than a specific value of alpha(⍺)
test statistic
based on a statistic that estimates the parameter that appears in the hypotheses
Decision Analysis
regards statistical inference in general as giving rules for making decision in the presence of uncertainty
power
measures its ability to detect an alternative hypothesis
type 1 error
occurs when we reject H_0 when it is in fact true
type 2 error
occurs when we accept H_0 when in fact H_a is true
acceptance sampling
one such circumstance that calls for a decision or action as the end result of inference