Exam 2

Question 1

Mean

Answer 1

average

Question 2

Median

Answer 2

mindpoint

Question 3

Mode

Answer 3

the most frequent

Question 4

Range

Answer 4

Difference between highest and lowest values

Question 5

Variance

Answer 5

Average of squared deviations from the mean

Question 6

Standard Deviation

Answer 6

• Square root of variance

- describes the variability of a single sample

Question 7

Frequency Distribution

Answer 7

Number of times that each value appears

Often converted to %

Question 8

Ex. What is your gender

• Level of measurement
• Central Tendency
• Variability

Answer 8

Level of measurement: Nominal
Central Tendency: Mode
Variability: Frequency

Question 9

Ex. Rank these five brands in order of your preference

• Level of measurement
• Central Tendency
• Variability

Answer 9

Level of measurement: Ordinal
Central Tendency: median, mode
Variability: frequency

Question 10

Ex. On a scale of 1 to 5 how does Starbucks rate on the variety of its drinks?

• Level of measurement
• Central Tendency
• Variability

Answer 10

Level of measurement: scale
Central Tendency: mean, median, mode
Variability: frequency, SD, range

Question 11

Ex. About how many times did you buy fast food for lunch last week?

• Level of measurement
• Central Tendency
• Variability

Answer 11

Level of measurement: scale
Central Tendency: mean, median, mode
Variability: SD, range

Question 12

Descriptive Statistics

Answer 12

are computed from information provided by a sample

Question 13

Statistical inference

Answer 13

uses sample statistics along with sample size to make inferences about a population

Question 14

Central-limit Theorem

Answer 14

• As sample size increases, distribution of sample means, randomly selected, approaches normal distribution
• If assume approximately normal distribution, can make inferences about a variable

Question 15

Standard error

Answer 15

represents the standard deviation of a theoretical sampling distribution of means

Question 16

How do we tell if a result is statistically significant?

Answer 16

How many standard errors away from the comparison value is your result?
- If more than two standard errors away from the comparison value, conclude the difference you found is unlikely to have occurred by chance and is therefore significantly different from the comparison value.

Question 17

Comparison value

Answer 17

is that difference in the population parameters is equal to zero—meaning there is NO DIFFERENCE between groups

Question 18

How Do You Know When the Results Are Significant?

Answer 18

If the result falls outside of 2 standard errors from 0, it is not likely that the true difference is 0. Rather, it is likely that there is a real statistical difference between the two means in the population.

In other words, there is such a large difference between the means that it probably didn’t occur due to chance (sampling error) and it is likely the result of a true difference in population means.

Question 19

ANOVA

Answer 19

Differences between three or more means from independent samples

Question 20

Paired Samples t test

Answer 20

Differences between means when there are two measures for each respondent like a brand rating pre/post viewing an ad

Question 21

Covariation

Answer 21

amount of change in one variable systematically associated with a change in another variable

Question 22

Correlation coefficient

Answer 22

• between the range of −1.0 and +1.0
• communicates strength and direction of linear relationship between two scale variables
  size indicates strength of association
• sign (+ or −) indicates the direction of association

Question 23

Coefficient Range:

+.81 to +1.0; -.81 to -1.0

Answer 23

Strong

Question 24

Coefficient Range:

+.61 to +.80; -.61 to -.80

Answer 24

Moderate

Question 25

Coefficient Range:

+.41 to +.60; -.41 to -.60

Answer 25

Weak

Question 26

Coefficient Range:

+.21 to +.40; -.21 to -.40

Answer 26

Very Weak

Question 27

Coefficient Range:

+.20 to -.20

Answer 27

None

Question 28

correlation analysis requires….

Answer 28

two scale level variables

Question 29

Regression analysis

Answer 29

is a predictive analysis technique in which one or more variables are used to predict the level of another by use of the straight-line formula

Question 30

Bivariate regression

Answer 30

means only two variables are being analyzed, and researchers sometimes refer to this case as “simple regression.”

Question 31

Independent variable

Answer 31

used to predict the dependent variable (x in the regression equation)

Question 32

Dependent variable

Answer 32

that which is predicted (y in the regression equation) (text calls it the “criterion variable”)

Question 33

Y = a + bx

What does each component mean?

Answer 33

Y is dependent
A is intercept
B is slope
X is independent

Question 34

Dummy variable

Answer 34

nominal variable that can be shown as either a 0 or 1 (ie if January then 1 otherwise 0)

Question 35

R-square

Answer 35

(aka coefficient of determination), is a measure of the strength of the linear relationship in multiple regression
- Indicates how well the independent variables can predict the dependent variable.

Question 36

Independence assumption

Answer 36

the independent variables must be statistically independent and uncorrelated with one another (the presence of strong correlations among independent variables is called multicollinearity).