W5 - 1-Way Independent ANOVA

Question 1

Define experimental power

Answer 1

Ability to detect an effect of a certain size

Question 2

What do underpowered studies leave you unable to do?

Answer 2

Detect small effects

Question 3

What can you do to ensure the study has enough power?

Answer 3

Test plenty of people

Question 4

Type 1 error

Answer 4

Incorrect rejection of the true null hypothesis

When 1 concludes a relationship or effect exists when it actually doesn’t.

Question 5

What is the level of type 1 error we are willing to risk called?

Answer 5

Alpha

Type 1 errors will occur 5% of the time (1 in 20).

Question 6

Type 2 error

Answer 6

Failure to reject false null hypothesis

When 1 concludes a relationship or effect doesn’t exist when actually it does.

Question 7

What is the level of type 2 error we are wiling to risk called?

Answer 7

Beta

Question 8

What are statistical tests based on the assumption of?

Answer 8

That variance is due to true and random effects

Question 9

List reasons as to why you may have a p value larger than 0.05

Answer 9

No actual effect

Lack of power - Too small a sample to detect an effect of a certain size

Inadequate variability w/in IV

Measurement error

Nuisances variance

Question 10

List some sources of measurement error

Answer 10

Inadequate measurement instruments

Response error from participants

Contextual factors

Question 11

Equation for family wise error

Answer 11

1-(1-alpha)^no. tests conducted

Question 12

What happens to familywise error with the increasing number of tests we run

Answer 12

More inflation of familywise error rate

Question 13

How can the increased family wise error/error rate be corrected?

Answer 13

By the bonferroni, Tukeys HSD, Holm & Scheffe tests

Question 14

What do the bonferroni, Tukeys HSD, Holm & Scheffe tests do?

Answer 14

Reduce your ability to detect a true effect

Lower experimental power

Increase chance of making a type 2 error

Question 15

What is a solution to the bonferroni, Tukeys HSD, Holm & Scheffe tests lowering experimental power + increasing chance of making a type 2 error?

Answer 15

1-way independent ANOVA

Question 16

What does the 1-way independent ANOVA allow you to do?

Answer 16

Compare many groups w/ a single test

Question 17

Positives to a 1-way independent ANOVA

Answer 17

No inflated familywise error rate

No reduction in experimental power

Question 18

Assumptions to the 1-way independent ANOVA

Answer 18

Samples are independent

Data is interval or ratio

Normally distributed

Homogeneity of variance

Question 19

What is the variance in ANOVA tables?

Answer 19

Mean Square (MS)

Question 20

What does ANOVA ask the question of?

Answer 20

How successful the experimental manipulation has been in comparison to the natural variability that exists.

Compares the type of variance you want (effect variance) with the variance you do not want (error variance).

Question 21

What is the F ratio

Answer 21

Ratio between wanted (effect) variance and unwanted (error) variance.

Question 22

What does the 1-way independent ANOVA do specifically?

Answer 22

Examines the ratio of variance between groups + variance within groups

MS between / MS within

Question 23

When do significant effects occur in the 1-way independent ANOVA

Answer 23

When you have 4 times as much variance between groups than within.

Question 24

What does an F ratio close to 1 mean?

Answer 24

Treatment creates little variability in scores

Question 25

When can a significant difference be shown in regards to the F ratio

Answer 25

When theres a large F statistic but depends on the df

Question 26

Can the F ratio ever be negative?

Answer 26

NO

Question 27

Is the F ratio ever less than 1

Answer 27

Hardly ever

Question 28

What size are most F ratios

Answer 28

Medium

Question 29

What does a small F ratio usually indicate

Answer 29

No effect

Question 30

What does a large F ratio usually indicate?

Answer 30

A sig effect but depends on df

Question 31

How can you find out if the F ratio is sig?

Answer 31

Calculate df between groups (effect/treatment) Calculate df within groups (Error) Find values on critical value table. If F value is larger than the critical value for our df then there IS a sig difference at the p<0.05 level.

Question 32

Why is error variance (a.k.a measurement error) always present?

Answer 32

Due to variables not being able to be measured perfectly + there being ind differences

Question 33

Error variance (MSE) in independent ANOVA

Answer 33

Always occurs within each group (MSwithin)

Question 34

Calculating the F ratio How to calculate the SS within

Answer 34

Mean of each group Subtract mean from a dataset from each value in that dataset. Square the differences Total the squared differences to get the SS within.

Question 35

Calculating the F ratio How to calculate the SS between

Answer 35

Sum of means Square of means Total the squared means Calculate SS for means of the groups (SSm) Multiply SSm by no. of ppl in each group to give the between group effect (variance)

Question 36

What must happen if the F value is greater than the critical value of 3.68?

Answer 36

Reject null hypothesis as there IS a sig difference at the p<0.05 level Meaning 1 of our mean values is sig different from 1 of the other sample means. but don't know which as theres more than 2 groups so we need to carry out a POST HOC TEST

Question 37

What are post hoc tests used to determine?

Answer 37

Which pairs of means are different from 1 another

Question 38

List the post hoc tests

Answer 38

Tukeys HSD test Bonferroni Correction test - Usually this one Scheffe test LSD test

Question 39

How is effect size reported?

Answer 39

Partial eta squared

Question 40

Define effect size

Answer 40

% of variability in the DV explained by the IV.

Question 41

Which post hoc tests provides the most conservative correction?

Answer 41

Bonferroni

Question 42

What does the Bonferroni post hoc test do?

Answer 42

Counteracts inflated familywise error by creating a new alpha. Does this by dividing original alpha by no. of tests conducted.

Question 43

When must you avoid using the Bonferroni post hoc test

Answer 43

When theres lots of conditions

Question 44

What does the Tukey HSD post hoc test do?

Answer 44

Calculates a new critical value

Question 45

When should the Games-Howell test be used?

Answer 45

When you have unequal variances between groups due to levenes test p value being <0.05.

Question 46

What does the LSD post hoc test stand for?

Answer 46

Least sig difference Should be avoided