PSY 295 exam multiple choice questions

For the general population of high school students, the average SAT math score is 500 with a

standard deviation of 100. A sample of high school students are selected from the general

population of high school students and are given a 6-week SAT prep course. If the prep course is

effective in improving their SAT scores, then:

the sample mean should be a lot more than 500 and should lead you to reject the null

hypothesis

Which of the following makes a confidence interval narrower?

increasing the sample size

An instructor for an SAT prep course claims that students who complete the course will score

significantly higher on the verbal section of the SAT than the average high school student

(population mean = 500). A sample of students who completed the prep course got an average

SAT verbal score of 530. The 95% confidence interval (CI) for that sample is 495 to 565.

Which of the following statements is true?

The instructor's claim is not supported by the data because 500 is within the CI

If you increase your alpha level (e.g., increase it from .01 to .05) for a t-test, which of the

following will occur?

Your critical t-value will decrease

Which of the following would make it MORE likely that you would reject the null hypothesis

in an independent samples t-test?

You decide to increase the alpha level from .01 to .05.

To test the hypothesis that students would be better at recognizing actors than politicians,

students were shown photos of either actors or politicians and asked to write down the name of

each of each person. On average, students in the actors condition recognized 4.2 more people

than students in the politicians condition. The 95% CI for the mean difference in number of

correct answers was 1.5 to 6.9. We can conclude that:

The two groups significantly differ because 0 is not in the CI

A Type I error is

Rejecting a true H0

A Type I error can be described as ______, while a Type II error can be described as _______.

a false positive; a false negative

Which of the following would lead to increased power for a statistical test?

A smaller standard error

As Type I error increases, Type II error ___________ and power _________

decreases; increases

Is there a difference between psych majors and non-majors in intro psych

exam scores?

Independent groups t-test

Did students in this class do better on exam 1 than they did on exam 2?

Dependent groups t-test

The population of adult males in the US has a mean height of 70 inches and

a standard deviation of 3 inches. A researcher wants to know if men raised

in poverty grow up to be shorter than average, so he compares the height of

a sample of men who grew up in poverty to this national average.

One-sample z-test

Who has the largest number of friends, cat owners or dog owners?

Independent groups t-test

People are asked to rate, on a 7-point scale, how much they like a two

different types of animals: Cats and dogs. Is there a difference between how

much people prefer each type of animal?

Dependent groups t-test

A researcher is interested in the effects of music choice on cognitive

performance. Participants perform a cognitive task (which can be scored up

to 100 pts) while listening to soothing music, or loud rock music.

Independent groups t-test

The average SAT score (reading and math combined) in the US is 1060 with

a standard deviation of 100. The owner of an SAT test prep company wants

to know if students who take her class score above the population average.

She compares a sample of students from her course to this population

average

One-sample z-test

Does adolescents’ agreement with their parents’ values (rated on a 50-point

scale) increase or decrease from age 17 to age 20 (attitudes measured at

both of those time points)?

Dependent groups t-test

A researcher studying the effectiveness of a new blood pressure medication

recruits participants and gives them either the new medication or a placebo

and then measures their blood pressure.

Independent groups t-test

The owner of a laptop battery manufacturing plant has produced

batteries with an average life of 4 hours. He recently changed the

manufacturing process and wants to make sure that the battery life is still 4

hours. So he tests the life of a sample of batteries manufactured with the

new method and compares their average life to the traditional average of 4

hours

One-sample t-test

An elementary school teacher is trying out a new teaching technique.

In order to see if it’s effective, she measures her students reading skills both

before and after she starts the new technique

Dependent groups t-test

One-sample z

One sample mean, compared to a specific

comparison population where the population SD is known

One-sample t

One sample mean, compared to a specific

comparison population where the population SD is

unknown

Independent t

Two separate groups of people

Related t

within-subjects or paired subjects

What is the sampling distribution of the mean?

theoretical probability distribution of all possible sample means of a specific size that could be drawn from a population

What are the general characteristics of the sampling distribution of the mean, including

the mean and SD of the sampling distribution?

The Shape: If the population is normal, or if the sample size is large enough (

), the distribution will be normal.

The Mean (

): The mean of the sampling distribution is equal to the mean of the population (

). This is known as being an "unbiased estimator."

The Standard Deviation (

): Also called the Standard Error (SE), it is calculated as

What does the Central Limit Theorem (CLT) state?

The CLT states that regardless of the shape of the population distribution, the sampling distribution of the mean will approach a normal distribution as the sample size increases

What affects the size of the Standard Error?

population standard deviation and sample size

What is the purpose of hypothesis testing?

To determine if the results found in a sample are strong enough to justify making a conclusion about the entire population, or if they could have just happened by chance

When do we make a decision to reject/accept the null?

Reject: If your calculated test statistic (like

or falls in the critical region (the "tail" beyond the alpha level).

Fail to Reject: If your statistic falls in the main body of the distribution.

What does it mean when we accept or reject the null?

Reject

: You found a "statistically significant" effect; the treatment worked or the group is different.

Fail to Reject

: You do not have enough evidence to say there is an effect. (Note: We never "accept" the null; we just fail to find enough evidence against it).

What are the “alpha level” and the “critical region”?

Alpha: The probability of making a Type I error (usually .05). It's the "cutoff" for how rare a result must be to be considered significant.

Critical Region: The area in the tails of the distribution defined by alpha. If your sample mean falls here, it's very unlikely to have happened by chance.

What factors make it more/less likely that you’ll reject the null hypotheses (i.e., how do

the alpha level you set and the size of the mean difference, standard deviation, and

sample size affect the outcome of your hypothesis test?).

To increase the likelihood of rejecting (Finding significance): Increase sample size, increase the mean difference, or decrease the standard deviation

What is Cohen’s d and what determines if something is a small, medium, or large effect?

Measures the magnitude of the treatment effect independent of sample size.

Small: 0.2 | Medium: 0.5 | Large: 0.8

When is it appropriate to use a t-test instead of a z-test?

when the population standard deviation is unknown

What is r2 and what does it mean?

It measures the percentage of variance in the scores that is explained by the treatment/group difference

What is a confidence interval for the mean and what does it tell us?

A range of values that is likely to contain the true population mean. Tells us if the null hypothesis falls outside the confidence interval

What factors affect the width of the CI and what effect do they have on the width?

confidence level, sample size, standard deviation

What is the difference between a between-subjects design, within-

subjects design, and matched subjects design?

Between-Subjects (Independent Groups): Different people in each group (e.g., Group A gets a caffeine pill, Group B gets a placebo).

Maps to: Independent Samples t-test.

Within-Subjects (Repeated Measures): The same people are in both conditions (e.g., testing reaction time before and after caffeine).

Maps to: Related/Paired Samples t-test.

Matched Subjects: Different people are in each group, but they are paired based on a specific variable (e.g., matching two people with the same IQ, then splitting them into different groups).

Maps to: Related/Paired Samples t-test.

What are the assumptions of the independent groups and related groups

t-tests?

independent: independence, normality, and Homogeneity of Variance

related: normality and independence

What is homogeneity of variance and why is it important?

The assumption that the variance (spread) of the scores in the two populations being compared is roughly equal

What are the benefits of using a repeated measures design instead of an

independent groups design?

economy, power

What does the confidence interval for mean difference tell us?

It provides a range of values that likely contains the true difference between the two population means.

When you calculate a confidence interval for a mean difference, how can

you know based on this interval, whether to accept or reject the null

hypothesis?

If the interval includes zero (e.g., -2.5 to +1.2), you fail to reject the null hypothesis (the difference might be zero).

If the interval does NOT include zero (e.g., +1.5 to +4.8), you reject the null hypothesis (the difference is statistically significant).

What is a type I error and what symbol is used to represent the type I error rate?

Rejecting the null hypothesis when it is actually true (a "false positive").

How is the type I error rate determined?

The rate is set by the researcher before the study

What is type II error and what symbol is used to represent the type II error rate?

Failing to reject the null hypothesis when it is actually false

What is power?

The probability of correctly rejecting a false null hypothesis

How are Type I error, Type II error, and power related to each other?

As you make a stricter (e.g., from .05 to .01) to avoid a "false positive," you naturally increase the risk of a "miss"

What factors affect type II error rate and power and what effect do they have?

sample size, alpha level, effect size, test type, pop variance