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PSY2005 > Variability, uncertainty and inferences > Flashcards

Variability, uncertainty and inferences Flashcards

1
Q

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?

A

sampling variation

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2
Q

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

A

standard deviation

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3
Q

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

A

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

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4
Q

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

A

unsystematic, systematic

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5
Q

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

A

how much of the total variance is unsystematic

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6
Q

what gives a graphical representation of variation in scores?

A

error bars

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7
Q

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

A

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

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8
Q

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

A

there is no overlap between groups

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9
Q

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

A

sampling error and unsystematic variation

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10
Q

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

A

standard error

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11
Q

what does a large standard error value indicate?

A

there is lots of variation

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12
Q

unsystematic variance = ? systematic variance = ?

A

error, effect

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13
Q

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

A

error (unsystematic variation), effect (systematic variation)

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14
Q

total amount of variance =

A

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

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15
Q

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

A

unlikely to be an effect in pop > small effect size

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16
Q

uncertainty = ______ / ______

A

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

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17
Q

what does the t test compare?

A

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

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18
Q

from what value can we calculate the p value?

A

from the t value we can calculate the p value

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19
Q

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

A

p value

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20
Q

what does a p value of less than 0.05 mean?

A

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!!

21
Q

why do we conduct inferential statistics?

A

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

22
Q

why do we not test qualitative data using inferential stats?

A

the focus is on subjective experiences

23
Q

why can inferential stats result in flawed estimates of error?

A

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

24
Q

size of effect =

A

mean difference

25
Q

what are the 3 measures of effect?

A

statistical significance, 95% confidence interval, effect size

26
Q

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

A

effect size

27
Q

what do the 3 measures of effect individually measure?

A

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

28
Q

what is the specific effect size for t tests?

A

cohen’s D

29
Q

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

A

small value > not much difference > no big effect

30
Q

low overlap of cohen’s d?

A

high value > more difference > more of an effect

31
Q

in an ANOVA what are independent variables called?

A

factors (and groups are called levels)

32
Q

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

A

the treatment effect

33
Q

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

A

independent t test, independent 1 way ANOVA

34
Q

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

A

between group variance

35
Q

how is the grand mean calculated?

A

the mean of each group mean

36
Q

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

A

grand, group

37
Q

how do you calculate between group differences?

A

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

38
Q

what do between group differences include?

A

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

39
Q

how is within group variance different from between group variance?

A

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

40
Q

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

A

F ratio

41
Q

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

A

F ratio

42
Q

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

A

greater

43
Q

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

A

smaller

44
Q

the np2 value is converted into a ______

A

proportion e.g. 0.45 > 45%

45
Q

what does np2 tell us?

A

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

46
Q

variability in data results in ______

A

uncertainty

47
Q

to compare effect sizes what do we need to use?

A

standardised measures of effect size

48
Q

what does a 1 way ANOVA tell you?

A

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

49
Q

what does it mean the ANOVA outcome is not significant?

A

there are no differences between groups

PSY2005 (12 decks)

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