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18 Cards in this Set
 Front
 Back
Acceptance sampling

Statistical procedure used in quality control and involves testing a batch of data to determine if the proportion of units having a particular attribute exceeds a given percentage.


Alternative hypothesis

Denoted by H1 or Ha, is the hypothesis that sample observations are influenced by some nonrandom cause.


Confidence Interval

Is an interval estimate combined with a probability statement;
statisticians use a confidence interval to express the degree of uncertainty associated with a sample statistic. 

Confidence level

Refers to the percentage of all possible samples that can be expected to include the true population parameter.


Critical values

A factor used to compute the margin of error.


Hypotheses testing

A test that defines a procedure that controls the probability of incorrectly deciding that a default position (null hypothesis) is incorrect based on how likely it would be for a set of observations to occur if the null hypothesis were true.


Level of significance

The likelihood that a statistical test will reject the data and hypothesis, despite the hypothesis actually being true.


Margin of error

Expresses the maximum expected difference between the true population parameter and a sample estimate of that parameter. To be meaningful, the margin of error should be qualified by a probability statement (often expressed in the form of a confidence level).


Null hypotheses

Denoted by H0, is usually the hypothesis that sample observations result purely from chance.


Onesample z statistic

Any statistical test for which the distribution of the test statistic under the null hypothesis can be approximated by a normal distribution.


Power

The power of a statistical test is the probability that the test will reject the null hypothesis when the alternative hypothesis is true (i.e. the probability of not committing a Type II error).


Pvalue

The probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.


Sample size

The number of individuals included in a statistical survey.


Significance level

The probability that an effect is not likely due to just chance alone.


Statistical significance

A result is considered significant not because it is important or meaningful, but because it has been predicted as unlikely to have occurred by chance alone.


Type I error

Is the incorrect rejection of a true null hypothesis; it is a false positive.


Type II error

Occurs when the null hypothesis is accepted, but the alternative is true; that is, the null hypothesis, is not rejected when it is false.


Z statistic

A test score converted or transformed into a common scale, such as standard units, to effect a more reasonable scale of measurement in order to make comparisons between different tests; also known as standard measure.
