Chapter 9 LearnSmart
A Type 1 error occurs if we DONT reject the null hypothesis when it is actually false
false
A type 2 error occurs when we
do not reject the null hypothesis when it is actually false - miss
we dont reject the null hypothesis when the p-value is
greater than or equal to a
The normal distribution approximation for a binomial distribution is valid when
np greater than and equal to 5 and n(1-p) greater than or equal to 5
In hypothesis testing, two incorrect decisions are possible:
- Not rejecting the null hypothesis when it is false - rejecting the null hypothesis when it is true
steps to use when formulating the null and alternative hypotheses
- include some form of the equality sign in the null hypothesis - determine whether it is one-or a two-tail test - identity the population parameter of interest
steps in the p-value approach to hypothesis testing in the correct order
1) specify the null and alternative hypotheses 2) calculate the value of the test statistic and its p-value 3) state the conclusion and interpret results
the power of a test is measured by
1- beta
specify the competing hypotheses that would be used in order to determine whether the population mean id less than 150
Ho: u> 150 vs. Ha: u<150
the significance level is the probability of making
a type 1 erroe
The conclusions of a hypothesis test that are drawn from the p-value approach versus the critical value approach are
always the same
an important final conclusion to a statistical test is to
clearly interpret the results in terms of the initial claim
an alternative hypothesis
contradicts the status quo
the two equivalent methods to solve a hypothesis test are the
critical value approach, pf-value approach
we can generally reduce Type 1 and Type 2 errors by
increasing the sample size
a binomial distribution can be approximated by a ____ distribution for large sample sizes
normal
The p-value is calculated assuming the
null hypothesis is true
The basic principle of hypothesis testing is to first assume that the ____ hypothesis is true and then determine if the sample data ___ this assumption
null. contradicts
if the chosen significance leave is alpha=.05, then there is 5% chance of
rejecting a true null hypothesis
We use hypothesis testing to
resolve conflicts between two competing opinions
Hypothesis testing enables us to determine if the collected ___ data is inconsistent with what is stated in the null hypothesis
sample
The power of a test is defined as
the probability of rejecting the null hypothesis when the null hypothesis is false
In hypothesis testing, two correct decisions are possible
- Rejecting the null hypothesis when the null hypothesis is false - Not rejecting the null hypothesis when it is true
The null hypothesis is specified by using one of the following signs
=, less than or equal, greater or equal to
The hypothesis denoted by Ho is the ___ hypothesis and the hypothesis denoted by Ha is the ___ hypothesis
Null, alternative
if the value of the test statistic falls in the rejection region, the p-value must be
less than alpha
the expected value of the sample distribution of p-bar 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
if the population standard deviation is unknown, it can be estimated by using
s
In a two-tailed test, we can reject the null hypothesis on either side of the hypothesized valued of the population parameter
true
The optimal values of type 1 and type 2 errors require a compromise in balancing the costs of each type of error
true
The alternative hypothesis for a two-sided test for a population mean would be denoted as
Ha: U doesnt equal Uo
In inferential stats, we use _____ information to make inferences about an unknown _____ parameter
sample, population
for a given sample size n, a Type 1 error can be reduced at the expense of a higher Type 2 error
true
we choose a value for ALPHA before conducting a hypothesis test
true
which of the following types of hypothesis tests may be performed?
Right-tailed, left-tailed and two-tailed tests
In hypothesis testing, if the sample data provides significant evidence that the null hypothesis is incorrect, then we
reject the null hypothesis
