Lecture 1

Question 1

Why are these techniques important?

Question 2

One-Way Between-Subjects Analysis of Variance Intro

Question 3

Bivariate regression analysis intro

Question 4

Multiple regression analysis intro

Question 5

Bivariate binary logistic regression analysis intro

Question 6

Multiple binary logistic regression analysis intro

Question 7

Summary table

Question 8

One-Way Between-Subjects
Analysis of Variance: Substantive hypothesis:

Answer 8

A person’s degree of organizational commitment (Y) depends on the team in
which the person works (X)

Question 9

Question for One-Way Between-Subjects
Analysis of Variance hypothesis

Answer 9

if the hypothesis is correct, what would you expect to find with
regard todifferences in average commitment between the teams?

Question 10

Key idea of ANOVA is:

Answer 10

When there are 2 or more groups, can we make a statement about possible
-significant- differences between the mean scores of the groups?

Question 11

Fundamental principle of ANOVA:

Answer 11

ANOVA analyses the ratioof the two components of total variance in data:
between-group variance and within-group variance

information on variance of average scores between groups
/
information on variance of scores within groups

ANOVA analyses ratio in which between-group variancemeasures
systematic differences between groups and all other variables that influence
Y, either systematically or randomly (‘residual variance’or ‘error’)

and

within-group variancemeasures influence of all other variables that influence
Y either systematically or randomly (‘residual variance’or ‘error’)

Question 12

Differences withina group

Answer 12

Any differences withina group cannotbe due to differences between
the groups because everyone in a particular group has the same group
score; so, within-group differences must be due to systematic
unmeasured factors (e.g., individual differences) or random
measurement error

Question 13

Differences between groups

Answer 13

Any observed differences between groupsare probably not only pure
between-group differences, but also differences due to systematic
unmeasured factors or random measurement error

Question 14

Null hypothesis

Answer 14

Mean scores of k populations corresponding to the groups in het study are
all equal to each other:
H : μ1= μ2=…= μk

Question 15

Why prefer One-Way Between-S ANOVA instead of seperate t-tests for
means(Warner, p. 220)?

Question 16

Why prefer One-Way Between-S ANOVA instead of seperate t-tests for
means(Warner, p. 220)?

Question 17

Formula for calculation of chance of 1 or more Type I errors in a series of
C tests with significance level α:

Question 18

F-distribution

Answer 18

In order to determine if a specific sample result is expectional (‘significant’)
under the assumption that the statistical null hypothesis is correct, the
test-statistic F has to be calculated

=testing hypothesis of variances.

Question 19

Deviation of individual score from grand mean:

Answer 19

Yij - My

Question 20

Deviation of individual score from group mean:

Answer 20

(Yij - Mi ) = εij

Question 21

Deviation of group mean from grand mean:

Answer 21

(Mi - My) = αiù
αi denotes the ‘effect of group i’(do not confuse with significance level!)

Question 22

(Yij - My) = (Yij - Mi) + (Mi - My)

Question 23

Sums of Squares

Question 24

Mean Squares

Answer 24

Sum of Squares/df:

(more on slides)

Question 25

F Ratio test statistic

Answer 25

MSbetween / MSwithin

Question 26

MSbetween formula

Question 27

MSwithin