Statistics Flashcards

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1
Q

what issue do stats mainly serve to solve?

A

to workout the likelihood that the results were obtain by chance

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2
Q

what shape is the probability distribution

A

bell curve

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3
Q

what does the null hypothesis help to determine?

what does it assume?

A

how unlikely our empirical result was under the chance distribution
null hypothesis assumes that result was all due to chance

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4
Q

what can we use to represent the chance distribution?

A

t-distribution and z-distribution

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5
Q

when can we only use z distribution?

A

when we know the population standard deviation

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6
Q

what is used when you do not know the population standard deviation?

A

t-distribution

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7
Q

what do you calculate the empirical t value

A

you take the difference between the observed mean, and the population mean, and divide it by the standard error of the mean

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8
Q

what is the population mean under the null hypothesis ?

A

zero

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9
Q

what changes the shape of the t distribution?

A

the degrees of freedom

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10
Q

smaller degrees of freedom change the shape of the t distribution by in what way?

A

the smaller the df, the “fatter” the tails will be, meaning more results cam call under this

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11
Q

….

A

the the observed t value, given the null hypothesis that t=0

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12
Q

what does a one sample design involve ?

A

comparing group data to known values (like IQ or “an hour” waiting time)

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13
Q

what is another name for a between groups design ?

A

an independent measures design

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14
Q

independent samples t test is used for…?

A

independent measures design

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15
Q

what is the main benefit of using an independent measures design

A

there will be no learning effects due to repeated exposure

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16
Q

what is the main 2 disadvantages of independent measures design?

A
  • people in different groups might greatly vary

- we cannot study how things can change overtime

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17
Q

what is another name for the within group design?

A

repeated measure design

18
Q

what are 2 main advantages of repeated measures designs?

A

baseline factors like personality etc don’t have to be accounted for as they will affect both conditions equally
- can study changes in behaviour over time

19
Q

what are 2 main disadvantages of repeated measures designs?

A
  • measurements are not independent
  • people cannot be naive in second round
  • need to factor in order effects (who does what condition first or second)
20
Q

what is the one sample t test formula?

A

M - u
t = ________

 S subscript M
21
Q

what is the formula to work out the standard error of the mean?

A

S
S (subscript) m = _______
square root
of n

22
Q

the standard deviation is what? how is it represented in formulas?

A

the square root of the variance

S

23
Q

how do we get the variance number?

A

the sum of squared differences divided by degrees of freedom

24
Q

why do we square the final value?

A

because we care about the magnitude not whether or not its above or below the mean

25
Q

t or f. the t value also quantifies the effect and tells us how strong the effect is

A

false

26
Q

what is the standard deviation formula?

A

SS
s^2= _____
df

then square root this number

27
Q

what is the t equation for the independent measures t test?

A

(Ma-Mb)-(ua-ub)
t= _____________
S subscript
(Ma-Mb)

28
Q

what is S

(Ma-Mb)

A

the difference between two means

standard error of the mean difference

29
Q

what is a key component of working out the standard error of the mean difference?

A

the pooled variance

30
Q

how do you calculate the pooled variance?

how does this look in a formula?

A

summing up the summed squared differences (SS) from each condition and dividing it by the sum of the df
SSa + SSb
s2p = ___________
df a + df b

31
Q

what is the short hand for pooled variance?

A

2
S
p

32
Q

the pooled variance is just what?

A

the average of the two sample variances

33
Q

what mean do we need to acquire in a paired samples t test ?

A

the difference mean
so we subtract the result from condition b from the result of condition a for all participants, and then find the mean of all these differences

34
Q

true or false, cohen’s d gives an estimate of effect size that is independent of sample size

A

true

35
Q

what does the d refer to in cohen’s d?

A

the mean difference divided by the standard deviation

36
Q

what are the conventional cut offs varying sizes in cohen’s d result?

A

small: 0.2-0.5
medium: 0.5 - 0.8
large: greater than 0.8

37
Q

what does r^squared mean?

A

variance explained

38
Q

True or false, r^2 is dependent on the sample size

A

true

39
Q

what is the formula for r^2

A

t^2
r^2= _______
t^2 +df

40
Q

what are the conventional cut offs of varying sizes in r^2

A

small: 0.01 - 0.09
medium: 0.09 - 0.25
large: bigger than 0.25

41
Q

what is a confidence interval?

A

setting parameters based on the assumption that the sample mean should be relatively near to the corresponding population parameter