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