W4 - Stats Refresher

Question 1

What are the 2 most commonly used parametric tests in experimental work?

Answer 1

ANOVA

T-tests

Question 2

Define variance

Answer 2

How spread out data is in relation to the mean + how close ind values are to the avg value.

Question 3

What is variance expressed as?

Answer 3

Sigma squared

Question 4

What is the variance of a data set describing?

Answer 4

Avg error between mean value + ind values of a data set

Question 5

What is population variance describing?

Answer 5

Variance of the entire pop of interest

Usually hypothetical unless we can measure every person in the pop

Question 6

How is population variance calculated?

Answer 6

Total deviance / Sample size

Question 7

Define sample variance

Answer 7

Variance of our experimental sample

Question 8

How is sample variance calculated?

Answer 8

Total deviance / degrees of freedom

Question 9

Which is smaller than which?

Sample variance or population variance

Answer 9

Population variance is always smaller than sample variance.

Question 10

What can be derived from variance?

Answer 10

SD

SEM

Question 11

What is SD equal to?

Answer 11

Square root of the variance

Question 12

Define SD

Answer 12

Variability of data around the mean

Question 13

What % of the population fall within 1 SD of the mean?

Answer 13

~68%

Question 14

What % of the population fall within 2 SD of the mean?

Answer 14

95%

Question 15

How is SEM or SE calculated?

Answer 15

SD / Square root of Sample size

Question 16

How might you examine variance in a visual manner?

Answer 16

By looking at error bars in graphs.

Question 17

Define deviance

Answer 17

How different each value is from the mean

Question 18

How is deviance calculated?

Answer 18

Calculate mean of data set

Each ind value - mean = deviance value

Square each deviance value

Add each squared deviance value to give the SS

Question 19

Define the SS

Answer 19

Total dispersion or deviance of scores from the mean

Question 20

Disadvantage to deviance

Answer 20

Size of deviance is dependent on how many values are in data set

Meaning its difficult to compare the SS from one data set to the SS of another data set with a different number of values.

Instead you would use avg dispersion rather than total dispersion. Avg dispersion is the variance.

Question 21

SPSS output

What does it mean when the skewness value is more than double the SE of skewness?

Answer 21

MAY have a skewed distribution

Question 22

SPSS output

What does it mean when the kurtosis value is more than double the SE of kurtosis?

Answer 22

May have a skewed distribution / non-normal distribution

Question 23

What are the statistical tests of normal distribution?

Answer 23

Kolmogorov-Smirnov test

Shapiro-Wilk test (better for sample sizes <50)

Question 24

What do statistical tests of normal distribution do?

Answer 24

Compare values in a sample to a normally distributed set of values with the same mean + SD.

Question 25

Statistical tests of normal distribution... p>0.05

Answer 25

Non-significant Distribution of sample isn't significant from a normal distribution so the distribution of data set is probably normal.

Question 26

Statistical tests of normal distribution... p<0.05

Answer 26

Significant Distribution of data is sig different from a normal distribution so the distribution of data set is probably NOT normal.

Question 27

What does it mean if tests indicate data is normally distributed?

Answer 27

Data meets the assumption of normality

Question 28

What if the data is not normally distributed?

Answer 28

Check + remove for outliers ONLY if you have good reason to believe that person does not belong to the population you want to sample. Use a non-parametric test (but means there will be a reduction in experimental power) Easy way to normality --> TEST MORE PEOPLE

Question 29

How can a data set be trimmed?

Answer 29

Prod a stem + leaf plot in SPSS to ID any outliers. Most researchers use 1 or 2 rules to trim the data set.

Question 30

What are the 2 rules most researchers use to trim the data set?

Answer 30

A % based rule SD based rule

Question 31

Trimming the data set What does the % based rule involve?

Answer 31

Deleting a certain % of the values in your data set i.e highest + lowest 10% Mean of that is then the trimmed mean.

Question 32

Trimming the data set What does the SD based rule involve?

Answer 32

Calculate mean + SD Remove values that are a certain number of SD from the mean

Question 33

What is the purpose of t-TESTS?

Answer 33

To give a value for the sig of the differences between the groups or conditions

Question 34

Independent samples t test

Answer 34

2 individual groups 2 experimental conditions + different participants assigned to each one

Question 35

Assumptions to the independent t test

Answer 35

Data is continuous Data is interval or ratio Both groups drawn at random from pop = independent Normally distributed data Homogeneity of variance between the samples

Question 36

Paired / 1 sample / Dependent t test

Answer 36

Comparing 1 group across 2 conditions

Question 37

Assumptions to the paired / 1 sample / dependent t test

Answer 37

Data is continuous Data is interval or ratio Differences are normally distributed Homogeneity of variance Both groups drawn at random from pop = Independent

Question 38

How is the output reported from SPSS for the independent samples t test

Answer 38

Each groups mean + SE/SD Mean difference + CI range T-value, df + p value t(df) = t, p = significance value

Question 39

How is the output reported from SPSS for the dependent/paired/1 samples t test

Answer 39

Each condition’s mean + SE/SD. Outline difference + the CI range T-value, df + p value.

Question 40

What is the t score/ t value

Answer 40

Difference between groups : difference within groups

Question 41

What does a larger t-score / t-value mean?

Answer 41

More difference between groups or conditions

Question 42

What does a smaller t-score / t-value mean?

Answer 42

More similarity between groups or conditions

Question 43

What would a t-value of 3 indicate?

Answer 43

Groups/conditions are 3 times as different from each other as they are within each other

Question 44

When running a t-test what does a bigger t value indicate?

Answer 44

More likely the results are repeatable.

Question 45

Define homogeneity of variance

Answer 45

Both groups have a similar spread of values around the mean

Question 46

Levene's test for homogeneity of variance When is the value for the levene's test NOT significant and what does this mean?

Answer 46

Not sig when p>0.05 So --> Accept assumption of homogeneity of variance Use equal variances assumed from SPSS

Question 47

Levene's test for homogeneity of variance When is the value for the levene's test IS significant and what does this mean?

Answer 47

p<0.05 Assumption of homogeneity of variance is violated Use equal variances not assumed

Question 48

Give an example of a 1-tailed test

Answer 48

Do people perform better under drug A than drug B

Question 49

Give an example of a 2-tailed test

Answer 49

Is there a difference in how drug A and drug B affect performance

Question 50

In theory, which tailed test has how much more statistical power to detect an effect than the other?

Answer 50

In theory, 1-tailed tests have twice as much statistical power to detect an effect.

Question 51

Which tailed test has more chance of finding a significant difference between groups or samples?

Answer 51

1-tailed tests

Question 52

Why do 1-tailed tests have more chance of finding a significant different between groups or samples than 2-tailed?

Answer 52

Because you need less participants to reach significance.

Question 53

In practise are 1-tailed tests used commonly?

Answer 53

No, rarely.