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Tests of Significance
assess the 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 za/2 with probability p lying to its right under the standard normal curve
Null Hypothesis
Says there is no effect or change in the population (H0)
Test for significance
intended to access the evidence provided by data against a null hypothesis
Alternate Hypothesis
says there is an effect or change in the population (Ha)
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 (not =)
p value
the probability that the test statistic will take a value as extreme or more extreme than the value actually observed.
Statistically significant
the p value is as small or smaller than a specified value
Test statistic
based on a statistic that estimates the parameter that appears in the hypothesis (z, t, p, x², or f)
Decision Analysis
regards statistical inference in general as giving rules for making decisions in the presence of uncertainty
Power
measures a significance test’s ability to detect an alternative hypothesis
Type I Error
occurs when we reject H0 when it is actually true
Type II Error
occurs when we accept H0 when Ha is actually true
Acceptance Sampling
one such circumstance that calls for a decision or action as the end result of inference
