Final Exam

Question 1

real limits

Answer 1

0.5 above the highest number and 0.05 below the lowest number

Question 2

frequency distribution, why is it useful

Answer 2

Present score values and their frequency of occurrence
shows the entire data

Question 3

ungrouped vs grouped freq. dist.

Answer 3

ungrouped: raw scores can be pulled out, can find individual score
grouped: raw scores cannot be pulled out, no individual score, information is lost

Question 4

relative frequency

Answer 4

proportion of total in interval
relative f = f/N
* should add up to 1

Question 4

cumulative frequency

Answer 4

number of scores that fall bellow the upper real limit
* start at the bottom then add up
* final answer should equal to N

Question 5

cumulative percentage frequency

Answer 5

Percentage of scores that fall below upper real limit of each interval
Cumulative % f= (f/N) x 100

Question 6

percentile point

Answer 6

% that falls bellow a specific percentage (P30 = 30% of scores fall below this point)

Question 7

percentile rank

Answer 7

percentage of scores with values lower than the score in question
ex: 10% of scores fall below 59

Question 8

bar graph vs histogram vs frequency polygon

Answer 8

bar graph: nominal and ordinal data, bars do not touch
histogram: interval and ratio data, bars do touch
polygon: interval and ratio data, point places above midpoint of each interval

Question 9

symmetrical vs positive vs negative

Answer 9

symmetrical: mean = median
positive: mean > median
negative: mean < median

Question 10

mean vs median vs mode

Answer 10

mean: is affected by outliers
median: is not affected by outliers
mode: used for nominal data

Question 11

correlation coefficient (pearson r)

Answer 11

specific measure of correlation, -1 to 1

Question 12

coefficient of determination (r^2) EFFECTSIZE

Answer 12

% of variability in one variable with is determined by its relationship with the other variable

Question 13

spearman rho

Answer 13

used for ordinary scaling

Question 14

assumptions for pearson r

Answer 14

only for interval and ratio scales

Question 15

regression

Answer 15

predicting

Question 16

regression line

Answer 16

to predict a score of one variable based on our knowledge of another

Question 17

regression constant

Answer 17

where the regression line crosses the y-axis

Question 18

conditions to use linear regression

Answer 18

• has to be linear
• random sampling
• predictions that lie within the range not outside
• not interest in the individuals that are used in the linear regression

Question 19

standard error of estimate

Answer 19

how far away, on average, a point will be from the regression line

Question 20

random sampling, why is it important?

Answer 20

equal chance of being selected, decreases error

Question 21

two ways to conduct random sampling

Answer 21

1. sampling with replacement
2. sampling without replacement

Question 22

sampling with replacement vs without

Answer 22

with: the selected is returned, doesn’t change the probability
without: the selected is not returned, changes the probability

Question 23

a priori vs a posterior (probability)

Answer 23

priori: before hand, based on rationalism
posteriori: after the fact, based on empiricism

Question 24

addition probability rule

Answer 24

p(A or B)= p(A) + p(B) - p(A and B) mutually exclusive: p(A) = p(B)

Question 25

multiplication probability rule

Answer 25

INDEPENDENT: p(A and B) = p(A) x p(B) DEPENDENT: p(A and B) = p(A) x p(B|A) Mutually exclusive: p(A and B) = 0

Question 26

independent vs mutually exclusive vs mutually exhaustive events

Answer 26

independent: does not influence e/o mutually exclusive: cannot happen at the same time, has to be OR mutually exhaustive: includes all possible events

Question 27

sampling distribution of F

Answer 27

used to evaluate mean differences between two or more treatments

Question 28

F distribution characteristics

Answer 28

- F-ratio is always positive - treatment effect is no greater than the variance expected by chance alone - for statistical significance obtained > critical

Question 29

Ho and H1 for one-way, independent groups ANOVA

Answer 29

Ho is true: effect is near zero, F is near 1.00 H1 is true: effect is more than 0, F > than 1.00`

Question 30

Why is MS between sensitive to the IV but not the MS within?

Answer 30

MS between uses df between which subtracts the IV by 1 while MS within uses df within which N is subtracted by IV

Question 31

assumptions for one-way ANOVA test

Answer 31

- 3 or more groups being compared - independent groups - IV is nominal and DV is interval or ratio - homogeneity of variance - N > 30

Question 32

omega^2 vs eta^2

Answer 32

omega^2 is less biased than eta^2 - both provide variance

Question 33

planned vs post hoc comparisons

Answer 33

planned (a priori): comparisons that are hypothesized before the experiment, based on theory and previous research post hoc (posteriori): comparison after seeing the data or to explore differences

Question 34

do planned or post hoc have more power?

Answer 34

planned comparisons have more bower but has a higher chance of type 1 error