Week 4

Question 1

what assumptions do we make about our sample?

Answer 1

• we take a single random sample
• we take a sample with reversion
• we take a sample from an infinitely large population

Question 2

sampling error

Answer 2

natural discrepancy between a sample statistic and its corresponding population parameter
- if n becomes larger, SE becomes smaller
- if SE becomes smaller, then M is getting closer to the population mean

Question 3

distribution of sample means

Answer 3

collection of sample means for all possible random samples of a size from a population

Question 4

characteristics of distribution of sample mean

Answer 4

• sample mean should be close to the population mean
• tend to form a normal-shaped distribution
• the larger the sample size, the closer the sample means should be to the population mean

Question 5

central limit theorem

Answer 5

provides a precise description of distribution if you selected every possible sample, calculated every sample mean and constructed the distribution of sample mean

Question 6

mean of the distribution of the sample means

Answer 6

• expected value of M = mean of the distribution of sample means is equal to the mean of the population of scores
• this is why M is an unbiased statistic

Question 7

standard error of M

Answer 7

standard deviation of the distribution of sample means

Question 8

null hypothesis

Answer 8

states that in the general population there is no change, no difference, and no relationship. independent variable does not affect the dependent variable

Question 9

alternative hypothesis

Answer 9

states that there is a change, difference, or relationship. independent variable influences the dependent variable

Question 10

alpha level/level of significance

Answer 10

probability value that is used to define the concept of “very unlikely” in a hypothesis test

Question 11

critical region

Answer 11

composed of extreme sample values that are unlikely to be obtained if null hypothesis is true. if sample data fall in the region, null hypothesis rejected

Question 12

type I error (false positive)

Answer 12

rejecting null that is actually true - treatment has an effect when in fact there is no effect
- alpha level determines the probability of type I error

Question 13

types II error (false negative)

Answer 13

failing to reject null that is false - treatment has no effect when, in fact, there is an effect
- beta level determines probability of type II error

Question 14

variability

Answer 14

larger variability produces a larger standard error and a smaller Z-score resulting in a lower likelihood of finding a sign

Question 15

number of scores

Answer 15

larger sample sizes produce a smaller standard error and a larger Z-score resulting in a higher likelihood of finding a sign