Variability, uncertainty and inferences

Question 1

data collected from humans is varied and this variability presents the challenge that any sample taken from the population is going to vary. What is this called?

Answer 1

sampling variation

Question 2

the value used to represent the natural variation between participant scores and sample means =

Answer 2

standard deviation

Question 3

what is standard deviation? (use words standardised and deviation)

Answer 3

it is the standardised measure of the amount of deviation we expect (the variation from the standard measure)

Question 4

the SD accounts for the _______ variance and the mean difference between experimental conditions accounts for the _______ variance

Answer 4

unsystematic, systematic

Question 5

what do we assess the effect (systematic variance) against?

Answer 5

how much of the total variance is unsystematic

Question 6

what gives a graphical representation of variation in scores?

Answer 6

error bars

Question 7

what do error bar graphs with 95% confidence interval provide?

Answer 7

an estimate of the effects we should find in a population e.g. we are 95% confident that the mean in the population will fall between the upper and lower CI

Question 8

what do we look for in error bar graphs to be 95% certain?

Answer 8

there is no overlap between groups

Question 9

what are the reasons that the sample mean will unlikely be the same as the population mean?

Answer 9

sampling error and unsystematic variation

Question 10

estimate of the deviation between our sample mean and population mean = ?

Answer 10

standard error

Question 11

what does a large standard error value indicate?

Answer 11

there is lots of variation

Question 12

unsystematic variance = ? systematic variance = ?

Answer 12

error, effect

Question 13

when running an inferential test we are looking at how much ____ and ____ there is

Answer 13

error (unsystematic variation), effect (systematic variation)

Question 14

total amount of variance =

Answer 14

total unsystematic V (due to ppts differing) + total systematic V (due to experimental manipulation)

Question 15

if there is more unsystematic variation what is the likely effect size and is there an effect?

Answer 15

unlikely to be an effect in pop > small effect size

Question 16

uncertainty = ______ / ______

Answer 16

effect / error (mean difference/standard error) THIS PROVIDES THE T VALUE

Question 17

what does the t test compare?

Answer 17

estimate of error against the effect (effect/error=t value)

Question 18

from what value can we calculate the p value?

Answer 18

from the t value we can calculate the p value

Question 19

whether we are likely to see an effect in the sample if there is no effect in the population =

Answer 19

p value

Question 20

what does a p value of less than 0.05 mean?

Answer 20

there is a very small chance of finding an effect in the sample if there is no effect in the population > this means there is a significant effect!!

Question 21

why do we conduct inferential statistics?

Answer 21

we need to generalise the effect to the population and make inferences about the effect in the population

Question 22

why do we not test qualitative data using inferential stats?

Answer 22

the focus is on subjective experiences

Question 23

why can inferential stats result in flawed estimates of error?

Answer 23

we haven’t tested the whole population so we don’t know the population mean and SD, and small samples won’t be representative of the population

Question 24

size of effect =

Answer 24

mean difference

Question 25

what are the 3 measures of effect?

Answer 25

statistical significance, 95% confidence interval, effect size

Question 26

standardised measure of how important the effect is that you find in the sample (magnitude of effect) = ?

Answer 26

effect size

Question 27

what do the 3 measures of effect individually measure?

Answer 27

p value = whether or not there is an effect, CI = estimate of effect you may have in the pop, effect size = compares the size of the effect

Question 28

what is the specific effect size for t tests?

Answer 28

cohen's D

Question 29

lots of overlap = small or large cohen's d?

Answer 29

small value > not much difference > no big effect

Question 30

low overlap of cohen's d?

Answer 30

high value > more difference > more of an effect

Question 31

in an ANOVA what are independent variables called?

Answer 31

factors (and groups are called levels)

Question 32

differences found due to the fact that ppts did different things in each of the groups =

Answer 32

the treatment effect

Question 33

1 IV with 2 conditions = ? 1 IV with 3 conditions = ?

Answer 33

independent t test, independent 1 way ANOVA

Question 34

differences between groups assumed due to the manipulation we have applied to the groups =

Answer 34

between group variance

Question 35

how is the grand mean calculated?

Answer 35

the mean of each group mean

Question 36

the between group variance is the difference between the ______ mean and each _____ group

Answer 36

grand, group

Question 37

how do you calculate between group differences?

Answer 37

take away each group mean from the grand mean, add these values together, square this value, multiple by n, divide by df

Question 38

what do between group differences include?

Answer 38

effect (differences due to manipulation), error (individual differences, sampling error)

Question 39

how is within group variance different from between group variance?

Answer 39

between = systematic variance (effect) compared to within = unsystematic variance > how much error we have in our effect. this error is due to individual differences and sampling error

Question 40

between groups variance (effect) / within groups variance (error) gives a value that represents the effect. what is this value called?

Answer 40

F ratio

Question 41

value that provides an indication of the size of our effect taking the error into account =

Answer 41

F ratio

Question 42

if F is ______ than 1 you have more effect than error

Answer 42

greater

Question 43

if F is ______ than 1 you have more error than effect

Answer 43

smaller

Question 44

the np2 value is converted into a ______

Answer 44

proportion e.g. 0.45 > 45%

Question 45

what does np2 tell us?

Answer 45

what proportion of our total variance is due to the treatment effect

Question 46

variability in data results in ______

Answer 46

uncertainty

Question 47

to compare effect sizes what do we need to use?

Answer 47

standardised measures of effect size

Question 48

what does a 1 way ANOVA tell you?

Answer 48

whether there are differences between your group (but not which groups differ or by how much)

Question 49

what does it mean the ANOVA outcome is not significant?

Answer 49

there are no differences between groups