week 3 presenting data Flashcards

1
Q

univariate

A

one variable

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2
Q

bivariate

A

2 variables

IV and DV

more than 2 relationships

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3
Q

multivariate

A

more than 2 variables

complex relationships

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4
Q

noise

A

not part of testing logic, but interferes with the tested variation and defines reliability of results

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5
Q

where does the IV go on a graph

A

x-axis

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6
Q

where does the DV go on a graph

A

y-axis

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7
Q

where does noise go on a graph

A

error bars

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8
Q

give an example of noise

A

individual differences

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9
Q

discrete data

A

integer values, potentially values eg number of cars in car park

no fractions or decimals

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10
Q

continuous data

A

infinitesimal, real numbers eg time, temp and height

can include fractions or decimals

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11
Q

what is the general rule for freedom

A

more freedom = more versatile but less organized

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12
Q

pie chart

A

continuous, ratio-scaled axis presented as a circle

can include discrete data shown as wedges/circular sectors

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13
Q

pro of pie chart

A

relate parts/wedges to the whole

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14
Q

cons of pie chart

A

limited to 2 sources of variation - no error bars

requires ratio-scales, but finite data to define beginning and end of circumference

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15
Q

pro of bar chart

A

highlighting distance from 0 or baseline = constant value

highlight differences across groups or conditions = nominal

visualise groups and conditions

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16
Q

cons of bar chart

A

no continuos X - one axis needs to be discrete

clutter with many scores

17
Q

pros of line chart

A

shows trends and relationship

as change in y…change in x

18
Q

cons of line chart

A

covariation - useless when multiple data points per x-value

less efficient for grouping than bars

19
Q

pros of scattergraph

A

covariation

visuals 2D measures, bivariate distribution

20
Q

cons of line graph

A

lacks structure

occlusion

free floating points - clutter

21
Q

what is aggregation by frequency

A

individual data points are grouped and summarized based on how often they occur within specific categories, intervals, or values

22
Q

steps for aggregation

A
  1. define categories
  2. count occurrence
  3. summarise data eg frequency table - can work out %
23
Q

where does frequency go on a graph

A

y-axis

24
Q

binning

A

transform continuous data into discrete data by allocating the continuous data to intervals (bins)

25
Q

histogram

A

a bar chart using bins to display continuous data

26
Q

how does negative skew look in a histogram

A

left tail is lower

27
Q

when do you use a histogram

A

for frequency and probability density

28
Q

frequency density

A

frequency of data per equal interval = frequency/bin size

29
Q

probability density

A

probability of data per value

30
Q

cumulative sum or running total

A

sum of frequencies progressively

31
Q

what type of graph would you choose if both IV and DV were qualitative (nominal or ordinal)

A

bar chart

32
Q

how to show standard deviation on a graph

A

standard error bars

33
Q

how can you represent an assymetrical distribution

A

box and whisper plot

34
Q

where is the outcome on a bivariate distribution

A

y axis

35
Q

where is predictor on a bivariate distribution

A

x axis

36
Q

when are mean and median the same

A

when the same number of values occurs on either side of the mean

37
Q

what does it mean when the distance between minimum and the mean is smaller than the SD

A

the distribution is positively skewed