L5 Data visualisation

Question 1

everything we measure carries a what?

Answer 1

element of uncertainty

Question 2

how do we account for random error?

Answer 2

reporting results with a margin of error

Question 3

what war was Florence Nightingale in?

Answer 3

Crimean

Question 4

what did Florence Nightingale do from July 1854 to end of 1855?

Answer 4

document:
- how many soldiers died
- what month they died in
- cause of death

Question 5

when was FN’s work published?

Answer 5

1858

Question 6

what did FN created? and what did this do?

Answer 6

visualisations of her data to send back to London
- was effective as allowed British army to see where deaths were preventable and where to allocate resources

Question 7

standard bar charts display -

Answer 7

categorical data clearly

Question 8

if a bar chart is not shown as a percentage when what does it not need to do?

Answer 8

= 100

Question 9

what are bar charts good for?

Answer 9

comparing the size of groups

Question 10

what is the difference in a cluster bar chart?

Answer 10

each year has a cluster of bars

Question 11

what is a cluster bar chart good at?

Answer 11

showing patterns

Question 12

are 3D bar charts good / should we use them?

Answer 12

no

Question 13

why are 3D bar charts so bad?

Answer 13

• look bad
• difficult to interpret
• difficult to directly compare the height of bars

Question 14

when are graphs more beneficial than tables?

Answer 14

when there is lots of information points and data
- i.e. different factors (years / places / etc.)

Question 15

what did Hans Rosling do?

Answer 15

help develop stats to do with health
- showed Govs. where to put money and resources

Question 16

do statistics prove things? what do they do?

Answer 16

no
- they help us understand how uncertain we should be about a measurement

Question 17

pie charts purpose = to

Answer 17

illustrate proportions

Question 18

pie charts show -

Answer 18

relative size of categories that add up to 100%

Question 19

who dislikes pie charts?

Answer 19

data scientists

Question 20

why do data scientists dislike pie charts?

Answer 20

as they take up a lot of space

Question 21

what can sometimes just show info better than pie charts?

Answer 21

tables

Question 22

histograms are normally used to display -

Answer 22

continuous numerical data

Question 23

what are histograms give us quickly?

Answer 23

an overview of the spread of data

Question 24

with histograms what are we interested in that’s different to bar charts?

Answer 24

the size of each bin - not height

Question 25

data is right skewed when is it....

Answer 25

bigger than median

Question 26

what are density plots similar to?

Answer 26

histograms

Question 27

draw what a density plot looks like:

Answer 27

.

Question 28

density plots are a what?

Answer 28

smoothed out version of a histogram

Question 29

what are density plots as if you did?

Answer 29

drew a freehand line over a histogram

Question 30

what does histograms show?

Answer 30

the distribution of a continuous variable

Question 31

box plots = a

Answer 31

standardised way of displaying the distribution of data on a five number summary

Question 32

what are box plots sometimes known as?

Answer 32

whisper plots

Question 33

what are box plots best at telling us about?

Answer 33

outliers and what their values are

Question 34

line graphs are used to represent -

Answer 34

2 continuous variables

Question 35

different lines show...

Answer 35

different things (i.e. countries)

Question 36

what are line charts often used to illustrate? - and example

Answer 36

financial data - i.e. stock market performance over time

Question 37

what is the x axis normally in line charts?

Answer 37

time

Question 38

what axis is time normally in line charts?

Answer 38

x

Question 39

what can line charts also sometimes show? - and example

Answer 39

demographic information - i.e. how life expectancy changes over time

Question 40

scatterplots are sometimes known as -

Answer 40

scattergraphs

Question 41

scatterplots are used to show -

Answer 41

2 continuous variables

Question 42

colour in scatterplots show?

Answer 42

different things

Question 43

example of a scatterplot =

Answer 43

-GDP per capita (x axis) -Life expectancy (y axis)

Question 44

example of use of different size plots in a scatterplot =

Answer 44

population size

Question 45

logarithmic scales also known as -

Answer 45

log scales

Question 46

what are log scales similar to?

Answer 46

scatterplots

Question 47

log scales PRO =

Answer 47

easier to differentiate than a scatterplot, as not all squeezed together

Question 48

log scales CON =

Answer 48

can be misleading + difficult to interpret

Question 49

do the media normally use log scales?

Answer 49

no

Question 50

(continuous data) Ordinal =

Answer 50

data that has natural ordering and hierarchy

Question 51

example of ordinal data =

Answer 51

satisfaction rating / level of agreement

Question 52

(continuous data) Nominal =

Answer 52

data has no natural ordering nor hierarchies

Question 53

example of nominal data =

Answer 53

gender / eye colour

Question 54

(categorical data) Discrete =

Answer 54

can take specific values + infinite options

Question 55

example of discrete data =

Answer 55

shoe size / age in years

Question 56

(categorical data) Interval =

Answer 56

infinite options, can take any value in a given interval

Question 57

example of interval data =

Answer 57

weight / percentage

Question 58

what do continuous variables measure?

Answer 58

things that vary continuously

Question 59

examples of continuous variables =

Answer 59

height / weight / income / age / mass

Question 60

continuous variables examples are most often seen in.....

Answer 60

nature

Question 61

categorical variables measure?

Answer 61

things that fall into categories

Question 62

categorical variable examples can often be seen in the....

Answer 62

social world

Question 63

true or false - continuous variables can be transformed into categorical ones

Answer 63

true

Question 64

true or false - data visualisations can mislead us (and intentionally sometimes?)

Answer 64

true

Question 65

truncating the axes =

Answer 65

shortening the height of the bars

Question 66

what does truncating the axes make it look like?

Answer 66

makes it look like there is a much larger gap than there is

Question 67

what is the problem with truncating the axes?

Answer 67

does not give a true representation of the difference between groups

Question 68

what does truncating the axes defeat the point of?

Answer 68

plotting a chart

Question 69

Beware also of d... a.....

Answer 69

dual axes

Question 70

dual axes can make things...

Answer 70

look more closely related than in reality they actually are

Question 71

dual axes can sometimes try and...

Answer 71

force relationships

Question 72

when it comes to dual axes us as the audience should always make sure to -

Answer 72

double check

Question 73

must also be aware of researchers being ............ about ......

Answer 73

selective about data

Question 74

researchers being selective about data can be -

Answer 74

misleading

Question 75

where can we often see researchers being selective about data?

Answer 75

in headlines

Question 76

x axis =

Answer 76

line on a graph that runs horizontally (left right)

Question 77

y axis =

Answer 77

line on a graph that runs vertically (up down)

Question 78

all axis' run through what?

Answer 78

zero

Question 79

what are the most common types of data visualisation

Answer 79

bar charts line charts scatterplots

Question 80

........ are an important part of data in the media

Answer 80

graphs