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PSYC1010 > shapes of distrib: transformations > Flashcards

shapes of distrib: transformations Flashcards

1
Q

what is the distribution shape

A

the curve enclosing the histogram

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2
Q

why do many people assume normal distribution

A

otherwise would have to examine and collect every member of pop data; impossible
makes easier for statistics

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3
Q

what does normal distribution look like

A

bell shaped; symmetrical

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4
Q

what is normal distribution

A

50% values on either side of mean
mean=median=mode
skewness and kurtosis= 0

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5
Q

what is asymmetrical data

A

skewed data

ranges from +∞ to -∞

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6
Q

what does it mean if a skew is greater than +-2

A

data is substantially skewed

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7
Q

what does it mean if the data has a standard error of skewness greater than 1.96

A

data is substantially skewed

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8
Q

what do measures of central tendency look like in a positive skew

A

mean>median>mode

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9
Q

what do measures of central tendency look like in a negative skew

A

mean

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10
Q

what is kurtosis

A

altitude of distribution

relative conc of scores in centre, upper and lower tails and shoulders

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11
Q

what is the range of kurtosis

A

-2 to +∞

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12
Q

what does -2 kurtosis mean for the figure of the grraph

A

flat

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13
Q

what does +∞ mean for the figure of the graph

A

peaked

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14
Q

what are the 3 types of kurtosis

A

mesokurtic
platykurtic
leptokurtic

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15
Q

what does mesokurtic mean

A

neutral degree; normal curve

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16
Q

what does platykurtic mean

A

flat; thick in shoulders

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17
Q

what does leptokurtic mean

A

peaked; thick in centre and tails

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18
Q

how can you tell that the distribution of data is significantly different from mesokurtic

A

if kurtosis divided by standard error of kurtosis is greater than 1.96

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19
Q

define modality

A

number of peaks

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20
Q

what are the 3 types of modality

A

unimodal
bimodal
multimodal

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21
Q

what does multimodal mean

A

more than 1 peak

22
Q

what does transforming data enable us to do

A

meet assumptions

23
Q

give an example of a transformation

A

take each score and multiply by itself

24
Q

which values are transformed in nonlinear transformations

A

all values for a particular variable

25
Q

what are the 3 nonlinear transformations to positively and negatively skewed data

A

square root
log
reciprocal

26
Q

what is the difference in nonlinear transformations between positively and negatively skewed data

A

at the beginning of neg skew transformation; must reflect the distribution then add constant so lowest value is 1.0
then at end reflect back so order of values is identical to original data

27
Q

what transformation do you apply to a moderate skew

A

square root each value

28
Q

what transformation do you apply to a substantial skew

A

logarithm each value

29
Q

what transformation do you apply to a severe skew

A

reciprocal transformation for each value of 1/x¡

30
Q

how do you retain order with reciprocal transformation

A

1/(xhighest - x¡)

31
Q

how do you avoid 0 with reciprocal transformations

A

1/(xhighest - x¡)

32
Q

is it cheating to transform data

A

no

33
Q

does nonlinear transformation change the shape of distribution of scores

A

yes

34
Q

does linear transformation change the shape of distribution of scores or effect stat anal; why

A

no because a constant is always

35
Q

what does linear transformation allow

A

expression of data in diff units and distrib shape stays same

36
Q

give examples of linear transformations

A

add sub a constant

mult div by a constant

37
Q

what does tabling the distribution mean we can do

A

give estimates of probability

38
Q

what is there a link between in data distribution

A

data distrib and prob of obtaining particular value in distribution

39
Q

what is the standard normal distribution for normal distribution

A 
mean= 0
SD= 1
40
Q

what does subtracting a constant from each score do to the mean of distrib

A

Reduce it by that constant

41
Q

what does dividing all values by a constant do to the SD

A

Divides SD by that constant

42
Q

what happens if you subtract the mean from all values in th distribution

A

gives mean of 0

43
Q

what happesn if divide all values in distrib by value of SD

A

gives SD of 1

44
Q

what does a Z score tell us

A

how many SD units a score is from mean

45
Q

what is the range of scores for z scores and where are most scores concentrated

A

-∞ to +∞

between -2 to +2

46
Q

what does the Z score magnitude tell us

A

how far the score is from the mean

47
Q

what is the Z score magnitude also known as

A

absolute value

48
Q

what Z score does the mean have in the standard normal distribution

A

0

49
Q

what does a positive Z score tell us

A

observation is more than mean

50
Q

what does a negative Z score tell us

A

observation is less than mean

PSYC1010 (10 decks)

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