Statistics Final

a hypothesis demonstrated in an indirect way using the hypothesis test. If the null hypothesis is rejected, this hypothesis is accepted.

Alternative hypothesis

A hypothesis is a claim or assumption about an unknown population parameter

Hypothesis

The quotient of the frequency at which a given characteristic occurs in a sample and the number of items in the sample

Sample proportion

The standard deviation of the distribution of sample means

Standard error of the mean

If a null hypothesis is not rejected at the .05 level of significance, the p-value is bigger than 0.05

True

The rejection and nonrejection regions are divided by a point called the critical value

True

Error committed by rejecting a true null hypothesis

Type I error

Error committed by failing to reject a false null hypothesis

Type II error

A statistical hypotheses consists of two parts

a null hypothesis and an alternate hypothesis

Generally speaking, new hypotheses that business researchers want to "prove" are stated in the

alternate hypothesis

hypothesis that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error

null hypothesis

The probability of getting a test statistic as extreme as the observed test statistic computed from the sample data under the assumption that the null hypothesis is true is called the

p-value

If the calculated test statistic falls in the rejection region, the statistical action is to

reject the null hypothesis

The probability of committing a Type I error is

the level of significance

Type II error is committed when

the null hypothesis is false and it is not rejected

Type I error is committed when

the null hypothesis is true and is rejected

When using the p-value to test hypotheses, the null hypothesis would be rejected if

the p-value is less than the significance level