Stats Chapter 9

the null hypothesis is specified by using one of the following signs:

=, <=, >=

a Type II error occurs when we:

Do not reject the null hypothesis when it is actually false

in hypothesis testing, two incorrect decisions are possible:

Not rejecting the null hypothesis when it is false, and Rejecting the null hypothesis when it is true

a Type I error occurs when we:

Reject the null hypothesis when it is actually true

True of False: in a two-tailed test, we can reject the null hypothesis on either side of the hypothesized value of the population parameter

True

True or False: the optimal values of Type I and Type II errors require a compromise in balancing the costs of each type of error

True

Ha

alternative hypothesis

what is NOT a step we use when formulating the null and alternative hypotheses?

calculate the value of the sample statistic

an alternative hypothesis...

contradicts the status quo

we can generally reduce Type I and Type II errors by:

increasing the sample size

if we reject the null hypothesis when it is actually false, we have committed:

no error

Ho

null hypothesis

the expected value of the sampling distribution of P_ is the:

population proportion

unlike the mean and standard deviation, the population proportion p is a descriptive summary measure that can be used for data that is:

qualitative

suppose the competing hypothesis..... 30

reject Ho and conclude.. .20 at 10%

in hypothesis testing, if the sample data provides significant evidence that the null hypothesis is incorrect, then we:

reject the null hypothesis

if the population standard deviation is unknown, it can be estimated by using:

s

In inferential statistics, we use _____ information to make inferences about an unknown _____ parameter

sample, population

a (alpha)

the probability of committing a Type I error

b (beta)

the probability of committing a Type II error

as a point estimate of the population proportion, we calculate:

p_