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25 Cards in this Set
 Front
 Back
What represents a Type I error?

Any time Ho is true and is rejected. This is a Type I error.


T/F
The null hypothesis represents the condition that will be assumed to exist unless sufficient evidence is presented to show the condition has changed. 
True
Assume the null hypothesis. Seek to show the alternative hypothesis is true. Innocent until proven guilty 

What represents a Type II error?

Type II errors are failing to reject a false null hypothesis.


What can be done to decrease both α and β?

Increase Sample Size


The probability that a hypothesis test will reject the null hypothesis when the null hypothesis is false is called

power


T/F
The necessary assumption for hypothesis testing is that data are nominal or ordinal 
False
Nominal or ordinal data cannot be used in hypothesis testing. The data must be interval or ratio level 

T/F
The null hypothesis is assumed to be false unless the evidence is strong enough to show that it is true 
False
The null hypothesis is assumed to be true 

T/F
When a new product is being tested the null hypothesis should be that the old product is at least as good as the new. 
True
Since the burden of proof is placed on the new product, the alternative hypothesis would support the new product's claim 

T/F
If the null hypothesis is rejected when it is, in fact, true, it is a Type I error 
True
Type II errors are failing to reject the null hypothesis when it is, in fact, false 

T/F
The significance level (designated by α) is the maximum probability of committing a Type I error 
True
The probability of committing a Type I error is α; the probability of committing a Type II error is β 

T/F
If α = 0.05 and the pvalue is 0.042, the null hypothesis should be rejected 
True
Reject the null hypothesis if the calculated pvalue is less than α 

T/F
β is the probability of accepting a false hypothesis 
True
β is the probability of committing a Type II error, accepting a false hypothesis 

T/F
A small business college claims that the average class size is equal to 30 students. To test this claim, nine classes were sampled and the class size of each was recorded. It is assumed that the population is normally distributed. A ztest would be the appropriate choice to test this claim 
False
Since the sample size is less than 30, the population standard deviation is unknown, and the population is normally distributed, the ttest would be the appropriate choice to test this claim 

T/F
If β in a hypothesis test was computed to be 0.3734 at a certain point, the power at that point is 0.6266 
True
Power = 1 – ß = 1 – .3734 = .6266 

T/F
If the pvalue is less than α, we do not reject the null hypothesis 
False
A small pvalue provides little support for the null hypothesis 

T/F
If a claim has been made about the population parameter and the decision maker is inclined to agree with the claim before gathering any data, the alternative hypothesis should be stated in support of the claim 
False
If a claim has been made about the population parameter and the decision maker is inclined to agree with the claim before gathering any data, the null hypothesis should be stated in support of the claim 

What can be done to reduce Beta?

Increase Alpha
Increase Sample 

Alpha and Beta have a(n) ________ relationship

Inverse


T/F
If the null hypothesis is rejected when it is, in fact, true, it is a Type I error. 
True
A Type I error rejects a true null hypothesis; a Type II error fails to reject a false hypothesis. 

T/F
If α = 0.05 and the pvalue is 0.042, the null hypothesis should be rejected. 
True
If the calculated pvalue is less than α, reject the null hypothesis. 

T/F
In a proportion study, p was found to be 0.09; n = 50 is large enough to be considered a large sample? 
False
np = .09(50) = 4.5 n times p should be greater than or equal to 5 

Which type of error occurred?
The Null hypothesis was rejected 
Type 1 Error


Which type of error occurred?
The Null hypothesis was not rejected 
Type 2 Error


Which type of error occurred?
The Null hypothesis, in reality, was true 
Type 1 Error


Which type of error occurred?
The alternative hypothesis, in reality, was true 
Type 2 Error
