TRUE OR FALSE: Though we often care about the claims made in the alternative (or research) hypothesis, we complete hypothesis tests to test the claims made in the null hypothesis.

TRUE OR FALSE: If we decide to retain the null hypothesis when there is evidence of a statistical relationship, we have committed a Type I error.

TRUE OR FALSE: When calculating inferential statistics, we can NEVER be 100% certain in our results because we are analyzing sample data.

TRUE OR FALSE: When writing out the null and alternative hypotheses using mathematical symbols (e.g., <), we ALWAYS use thePOPULATION parameternotation (e.g.,) to describe our predictions, even if we are using sample data to complete the hypothesis test.

which philosopher devised a theory about scientific knowledge and falsifiability (i.e., science confirms, pseudoscience disconfirms)?

Albert Einstein

Hank Green

Karl Popper

Sigmund Freud

A hypothesis test that tests whether a given mean is statistically different (or greater/less than) from some pre-determined value is called a...

two means test.

double hypothesis test.

single mean test.

single hypothesis test.

A friend claims that his average golf score over an 18-hole golf course is 63 strokes. One hypothesize that their friend's score is actually higher than he claims.

Question: Assuming that one were invested enough to collect sample data, what type of hypothesis test should one use to test their friend's claim?

single mean, one-tailed test

two means, two-tailed test

single mean, two-tailed test

two means, one-tailed test

The probability of making a Type I error is represented mathematically by the lowercase Greek letter...

delta

gamma

alpha

beta

My friend and I got into an argument about the relationship between pet type and happiness. My friend believes that people with dogs are more happy than people with cats. We decide to collect sample data and create a hypothesis test at the 99% confidence level. We write the following hypotheses:

H1: People with dogs are happier than people with cats. (dogs>cats)

H0: People with dogs are equally as happy or less happy than people with cats. (dogscats)

Question: What does an alpha level of 0.01 indicate in the context of the above hypotheses?

There is a 99% chance of concluding that people with dogs are happier than people with cats when, in fact, they are not.

There is a 1% chance of concluding that people with cats are happier than people with dogs when, in fact, they are not.

There is a 99% chance of concluding that people with cats are happier than people with dogs when, in fact, they are not.

There is a 1% chance of concluding that people with dogs are happier than people with cats when, in fact, they are not.

What decision should one make about the null hypothesis if the test statistic falls outside of the critical region (i.e., in the body of the sampling distribution of sample means)?

Reject the null hypothesis

Fail to reject (retain) the null hypothesis

From a 1995 study, a student learned that the average number of hours () spent watching TV by the entire US population aged 0 to 17 was 3 hours per day with a population standard deviation () of 5 hours. The student want to determine if the amount of time that kids spend watching television has changed since 1995.

She collect data on a random sample of 300 children in 2022 and find that, on average (x), they watch 5 hours of television per day. She decide to use this sample data to create a hypothesis test at the 95% confidence level.

Question: What kind of hypothesis test should she perform?

two means, one-tailed z-test

single mean, one-tailed z-test

single mean, two-tailed z-test

two means, two-tailed z-test

From a 1995 study, a student learned that the average number of hours () spent watching TV by the entire US population aged 0 to 17 was 3 hours per day with a population standard deviation () of 5 hours. She want to determine if the amount of time that kids spend watching television has changed since 1995.

She collect data on a random sample of 300 children in 2022 and find that, on average (x), they watch 5 hours of television per day. She decide to use this sample data to create a hypothesis test at the 95% confidence level.

Question: What is the alpha level?

5

0.01

0.05

1

From a 1995 study, a student learned that the average number of hours () spent watching TV by the entire US population aged 0 to 17 was 3 hours per day with a population standard deviation () of 5 hours. she want to determine if the amount of time that kids spend watching television has changed since 1995.

she collect data on a random sample of 300 children in 2022 and find that, on average (x), they watch 5 hours of television per day. she decide to use this sample data to create a hypothesis test at the 95% confidence level.

Question: What critical value(s)define the critical region?

-1.65

-1.96

+1.96 and -1.96

+1.96

+1.65

+1.65 and -1.65

From a 1995 study, a student learned that the average number of hours () spent watching TV by the entire US population aged 0 to 17 was 3 hours per day with a population standard deviation () of 5 hours. she want to determine if the amount of time that kids spend watching television has changed since 1995.

she collect data on a random sample of 300 children in 2022 and find that, on average (x), they watch 5 hours of television per day. she decide to use this sample data to create a hypothesis test at the 95% confidence level.

Question: What is the test statistic (Step 4)?

3.20

6.93

-2.86

4.29

From a 1995 study, a student learned that the average number of hours () spent watching TV by the entire US population aged 0 to 17 was 3 hours per day with a population standard deviation () of 5 hours. she want to determine if the amount of time that kids spend watching television has changed since 1995.

she collect data on a random sample of 300 children in 2022 and find that, on average (x), they watch 5 hours of television per day. she decide to use this sample data to create a hypothesis test at the 95% confidence level.

Question:Based on the critical region and test statistic that she found in the previous questions, what decision should she make about the null hypothesis?

Reject the null hypothesis

Fail to reject (retain) the null hypothesis