Basic Review

Question 1

Levels of measurement

Answer 1

1. Nominal
2. Ordinal
3. Interval
4. Ratio

Question 2

Nominal

Answer 2

Categories are mutually exclusive, but not ordered. Ex: species (cat, dog, fish, hermit crab)

Question 3

Ordinal

Answer 3

Order matters, but the difference between values is NOT informative. Ex: place in a race (1st, 2nd, 3rd,…)

Question 4

Interval

Answer 4

Order matters and difference between values IS informative. Ex: temperature (80, 90, 100)

Question 5

Ratio

Answer 5

Interval variable and true definition of zero. Ex: height, weight, pieces of candy eaten, NOT temp since there is still heat at 0 degrees.

Question 6

Measures of central tendency

Answer 6

1. Mean: The arithmetic average of scores in a dataset.
2. Median: The midpoint of scores in a dataset (when arranged in numerical order).
3. Mode: The most frequently occurring value(s) in a dataset.

Question 7

Measures of variability

Answer 7

1. Range
2. Standard deviation
3. Variance

Question 8

Range

Answer 8

Spread of scores in a dataset. Range = largest score - smallest score

Question 9

Standard deviation (SD)

Answer 9

How far the average score in the dataset is from the mean of that dataset. SD = √variance.

Question 10

Variance

Answer 10

SD squared

Question 11

Hypotheses

Answer 11

1. Null hypothesis (H0)

2. Alternative hypothesis (H1)

Question 12

Null hypothesis (H0)

Answer 12

Predicts no change, difference, or relationship. “The IV has no effect on the DV.”

Question 13

Alternative hypothesis (H1)

Answer 13

Predicts a change, difference, or relationship. “The IV has an effect on the DV.”

Question 14

Decision errors

Answer 14

Possibility of drawing incorrect conclusions from a study.

Question 15

Type I error

Answer 15

Incorrectly reject the null hypothesis (false positive). Conclude that treatment has an effect when it really doesn’t - there isn’t actually an effect.

Question 16

Type II error

Answer 16

Incorrectly retaining the null hypothesis (false negative). Conclude treatment doesn’t have an effect when it actually does.

Question 17

p-value

Answer 17

Indicates the likelihood that H0 is correct/that it would be a mistake to reject the null hypothesis. Indicates the probability/likelihood of your sample data when H0 is true.

Question 18

p < .05

Answer 18

Less than 5% chance that H0 is correct (low likelihood). Reject H0 if alpha = .05 (and retain if alpha is greater than .05).

Question 19

p < .01

Answer 19

Less than 1% chance that H0 is correct (very low likelihood). Reject H0 if alpha = .01.

Question 20

Effect size

Answer 20

Measures the size of treatment effect. “x% of the variability in the DV can be attributed to the IV”. Only compute if you reject H0/yield significant results!

Question 21

Power

Answer 21

Probability that the test will correctly reject a false H0; probability that the test will correctly identify a treatment effect if it exists. Influenced by effect size, sample size, alpha level and if the test is one or two-tailed.
As effect size increases, power increases. As sample size increases, power increases. As alpha level decreases, power decreases. A one-tailed test has more power than a two-tailed test.

Question 22

When to use a z-test

Answer 22

You have a nominal IV and want to compare the sample mean to the population mean when the population mean (σ) is known.

Question 23

When to use a one-sample t-test

Answer 23

You have a nominal IV and want to compare the sample mean to the population mean when the population mean (σ) is unknown.

Question 24

When to use an independent samples t-test

Answer 24

You have a nominal IV and want to compare two unrelated sample means to each other.

Question 25

When to use a dependent samples t-test

Answer 25

You have a nominal IV and want to compare two related sample means to each other.

Question 26

When to use correlation

Answer 26

You have an interval/ratio IV and want to examine the relationship/association between two variables.

Question 27

When to use regression

Answer 27

You have an interval/ratio DV and want to predict the DV using the IV.

Question 28

Z-test

Answer 28

Hypothesis test used to compare a sample mean to a population mean when the population SD is known.

Question 29

One-sample t-test

Answer 29

Hypothesis test used to compare a sample mean to a population mean when the population SD is UNknown.

Question 30

Independent-samples t-test

Answer 30

Hypothesis test used to compared two unrelated sample means to each other.

Question 31

Dependent samples t-test

Answer 31

Hypothesis test used to compare two related sample means to each other.

Question 32

ANOVAs

Answer 32

Hypothesis test used to compare 3+ unrelated sample means

Question 33

Correlation

Answer 33

Hypothesis test used to examine the relationship between two variables.

Question 34

Regression

Answer 34

Hypothesis test used to predict DV using IV.