PSYC 2111 Exam #2

Calculate Pearson r for the following data: Participant X Variable Y Variable 1 10 20 2 10 15 3 6 20

-0.5

My wife and I go to a dance. There are 100 people at the dance (98 people plus us). There are two door prizes at this dance. The door prizes are given by drawing your name out of a hat (assume that it is totally random). The drawing happens one at a time. After the first name is drawn, that person's name is put back in the hat. What is the probability that I will win the first door prize and my wife will win the second?

0.0001

My wife and I go to a dance. There are 100 people at the dance (98 people plus us). There are two door prizes at this dance. The door prizes are given by drawing your name out of a hat (assume that it is totally random). The drawing happens one at a time. After you win, your name is not put back in the hat. What is the probability that my wife and I will win both the first and second prize? (it doesn't matter who wins first and who wins second)

0.0002

The following data has a: Participant X Variable Y Variable 1 5 2 2 10 3 3 15 4 a) Positive, perfect relationship b) Negative, perfect relationship c) positive, imperfect relationship d)Negative, imperfect relationship

a) Positive, perfect relationship

Look at your answer from the last question. Assuming that α = .05, should you reject or fail to reject the null hypothesis? a) fail to reject the null hypothesis b) reject the null hypothesis

a) fail to reject the null hypothesis

I want to know if taking statistics makes you a better candidate for a job. I think that including statistics on your resume will make you a better job candidate. If I ended up determining that including statistics in your resume improved your rating as a job candidate, I would: a) reject the null hypothesis b) fail to reject the null hypothesis c)reject the alternative hypothesis d) fail to reject the alternative hypothesis

a) reject the null hypothesis

Look at your answer from the last question. Assuming that α = .05, should you reject or fail to reject the null hypothesis? a) reject the null hypothesis b) fail to reject the null hypothesis

a) reject the null hypothesis

I want to know if taking statistics makes you a better candidate for a job. I think that including statistics on your resume will make you a better job candidate. What would α be for these data? a) The probability of making a Type II Error b) the same as P(p) c) It's whatever we want it to be d) It is P(H)

c) It's whatever we want it to be

I want to know if taking statistics makes you a better candidate for a job. I think that including statistics on your resume will make you a better job candidate. What is the alternative hypothesis for this scenario? a) including statistics in your resume will not affect your job candidacy b)Improving your job candidacy will make you more likely to take statistics c) including statistics in your resume will make you a worse job candidate d) Including statistics in your resume will make you a better job candidate

d) Including statistics in your resume will make you a better job candidate

I want to know if taking statistics makes you a better candidate for a job. I think that including statistics on your resume will make you a better job candidate. If I fail to reject the null hypothesis, I could have: a) Been correct or made a Type I Error b) Made a Type II Error c) Made a Type I Error d) been correct or made a Type II Error

d) been correct or made a Type II Error

I want to know if taking statistics makes you a better candidate for a job. I think that including statistics on your resume will make you a better job candidate. What is the null hypothesis for this scenario? a) including statistics in your resume might make you a better job candidate b) Improving your job candidacy will make you more likely to take statistics c) Including statistics in your resume will make you a better job candidate d) including statistics in your resume will not affect your job candidacy

d) including statistics in your resume will not affect your job candidacy

Cut off for p-value significance is

if p is bigger or smaller than alpha

β is the most similar to:

r

The lower the P-value

the more likely you will reject the null (more probable that alternate hypothesis is correct)

Multiple regression can test the relationship between:

three predictor variables and one outcome variable

Use a single sample t test when

you know μ but not σ

My wife and I go to a dance. There are 100 people at the dance (including us). There are two door prizes at this dance. The door prizes are given by drawing your name out of a hat (assume that it is totally random). The drawing happens one at a time. After you win, your name is put back in the hat. What is the probability that someone from my family will win both of the prizes? (either I win both, my wife wins both, or we each win one in either order).

0.0004

There are 20 people in the room. 7 are wearing a hat, 12 are wearing glasses, 5 of the people who are wearing glasses are also wearing a hat. What is the probability of randomly choosing someone who is wearing a hat who is not wearing glasses?

0.1

Calculate Pearson r for the following data: Participant X Variable Y Variable 1 2 2 2 4 6 3 6 4

0.5

For the following data, what is Pearson r? Participant X Variable Y Variable 1 5 2 2 10 3 3 15 4

1

One continuous with one continuous (unstandardized)=

Linear regression

More than one continuous with one continuous=

Multiple regression

Df for t test =

N-1

Degree of freedom is always

N-2

One continuous with one continuous (standardized)=

Pearson's r

D-Bar=

average difference between the scores