Qmb3200 - Business Statistics - Test 2

Front 1

What represents a Type I error?

Back 1

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

Front 2

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.

Back 2

True

Assume the null hypothesis. Seek to show the alternative hypothesis is true.

Innocent until proven guilty

Front 3

What represents a Type II error?

Back 3

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

Front 4

What can be done to decrease both α and β?

Back 4

Increase Sample Size

Front 5

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

Back 5

power

Front 6

T/F

The necessary assumption for hypothesis testing is that data are nominal or ordinal

Back 6

False

Nominal or ordinal data cannot be used in hypothesis testing. The data must be interval or ratio level

Front 7

T/F

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

Back 7

False

The null hypothesis is assumed to be true

Front 8

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.

Back 8

True

Since the burden of proof is placed on the new product, the alternative hypothesis would support the new product's claim

Front 9

T/F

If the null hypothesis is rejected when it is, in fact, true, it is a Type I error

Back 9

True

Type II errors are failing to reject the null hypothesis when it is, in fact, false

Front 10

T/F

The significance level (designated by α) is the maximum probability of committing a Type I error

Back 10

True

The probability of committing a Type I error is α; the probability of committing a Type II error is β

Front 11

T/F

If α = 0.05 and the p-value is 0.042, the null hypothesis should be rejected

Back 11

True

Reject the null hypothesis if the calculated p-value is less than α

Front 12

T/F

β is the probability of accepting a false hypothesis

Back 12

True

β is the probability of committing a Type II error, accepting a false hypothesis

Front 13

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 z-test would be the appropriate choice to test this claim

Back 13

False

Since the sample size is less than 30, the population standard deviation is unknown, and the population is normally distributed, the t-test would be the appropriate choice to test this claim

Front 14

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

Back 14

True

Power = 1 – ß = 1 – .3734 = .6266

Front 15

T/F

If the p-value is less than α, we do not reject the null hypothesis

Back 15

False

A small p-value provides little support for the null hypothesis

Front 16

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

Back 16

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

Front 17

What can be done to reduce Beta?

Back 17

Increase Alpha
Increase Sample

Front 18

Alpha and Beta have a(n) ________ relationship

Back 18

Inverse

Front 19

T/F

If the null hypothesis is rejected when it is, in fact, true, it is a Type I error.

Back 19

True

A Type I error rejects a true null hypothesis; a Type II error fails to reject a false hypothesis.

Front 20

T/F

If α = 0.05 and the p-value is 0.042, the null hypothesis should be rejected.

Back 20

True

If the calculated p-value is less than α, reject the null hypothesis.

Front 21

T/F

In a proportion study, p was found to be 0.09; n = 50 is large enough to be considered a large sample?

Back 21

False

np = .09(50) = 4.5

n times p should be greater than or equal to 5

Front 22

Which type of error occurred?

The Null hypothesis was rejected

Back 22

Type 1 Error

Front 23

Which type of error occurred?

The Null hypothesis was not rejected

Back 23

Type 2 Error

Front 24

Which type of error occurred?

The Null hypothesis, in reality, was true

Back 24

Type 1 Error

Front 25

Which type of error occurred?

The alternative hypothesis, in reality, was true

Back 25

Type 2 Error