Visualising time series

Question 1

what is time series analysis

Answer 1

Time series analysis is about visualising the quantitative relationship through
time:

Question 2

2 examples of time series analysis

Answer 2

Business analysts hope to see profits increase over time

Government expects to see changes in relation to influential events

Question 3

Time gives us a context for understanding data so that present can be
_________ and future can be _______ in light of the past

Answer 3

understood, predicted

Question 4

what are the 6 basic time series patterns

Answer 4

–> Trend
–> Variability
–> Rate of change
–> Co-variation
–> Cycles
–> Exceptions

Question 5

what is trend

Answer 5

–> A trend is the overall tendency of a series of values to increase, decrease or
remain relatively stable during a particular period of time (like 12-months)

–> Any period of time can be the basis for determining a trend but the
comparison has to be within the same period

–> a trend can be shown by using lines of best fit based on statistical models

Question 6

what is variability

Answer 6

–> Variability is the average degree of change from one point in time to the next
throughout a span of time

Question 7

what is rate of change

Answer 7

–> This is useful when comparing multiple series of values.

–> Percentage difference is considered

Question 8

what is covariation

Answer 8

When 2 time series relate to one another so that changes in one are reflected as changes in the other, either immediately or later, is called co-variation.

Question 9

example of covariation

Answer 9

–> Daily average temperature (°F) for the city

–> Daily ice cream sales (number of ice creams sold) in the city

Question 10

what is cycles

Answer 10

Cycles are patterns that repeat at regular intervals, such as daily, weekly, monthly,
quarterly or seasonally

usually have a hockey stick pattern

Question 11

what are exception

Answer 11

Exceptions – values fall outside the norm

Question 12

what charts can be used in time series data

Answer 12

–> Bar charts
–> Dot plot
–> Radar charts
–> Heatmaps
–> Scatterplots (esp. in animation to analyse the correlation changes)

Question 13

what is a line chart used for in time series

Answer 13

For analysing Patterns and Exceptions

Question 14

what is a bar chart used for in time series

Answer 14

For Emphasizing and Comparing Individual Values

Question 15

what is a dot plot used for in time series

Answer 15

For analysing Irregular Intervals

The dots are NOT connected in a line. Mark
each value separately.

Question 16

what is a radar chart used for in time series

Answer 16

For comparing cycles and spot exception

Question 17

radar charts are also known as

Answer 17

spider charts

star charts

Question 18

what are heat maps used for

Answer 18

For analysing high volume cyclical Patterns and Exception

Question 19

what are scatterplots used for in time series analysis

Answer 19

Animated for analysing correlation changes

Question 20

what is discrete values

Answer 20

Discrete – values are from specific points or blocks of time
and there is a finite number of possible values

Question 21

eg of discrete values

Answer 21

E.g. Percentage of people who pass a test each year – this value don’t change afterward

Question 22

what is continuous values

Answer 22

Continuous – value that can be measured at any time of
day during any interval and it is constantly changing

Question 23

eg of continuous values

Answer 23

E.g. Environment or body temperature

Question 24

discrete time series data is best visualised in

Answer 24

Bar chart
Stacked Bar chart
Dot plot

Question 25

continuous time series data is best visualised in

Answer 25

Line chart
Step chart

Question 26

what are the 7 Techniques and Best Practices

Answer 26

–> Aggregating to Various Time Intervals
–> Viewing Time Periods in Context
–> Using Trend Line to enhance Perception of high-level Patterns
–> Omitting Missing Values from a display
–> Using Logarithmic Scales and Percentages to Compare Rates of Change
–> Overlapping time scales to Compare Cyclical Patterns
–> Stacking Line Charts to Compare Multiple Variables

Question 27

what is aggregating

Answer 27

–> Time-series data can look quite
different if you change the level of
aggregation.

–> There is a need to quickly and
easily switch between various
intervals of time to examine the
data and identify the insights

Question 28

what is context

Answer 28

–> Views of various time spans might
lead to insights that are not
available if we stick to one time
span.

–> Important to examine data in the
context of a longer period

Question 29

what is the trend line

Answer 29

–> Take note of the time period used
for the trend line

–> Be sure to examine values that fall
outside the specified time period
and not isolated a section that
would trend quite differently if the
period is altered

–> Usually a straight line is used and
based on linear regression

–> However it may not be the best fit
so may want to consider – running average

Question 30

what is the best practice for omitting

Answer 30

–> If missing values are found, we
can estimate the value or omit it
from displaying.

–> It is not right to treat missing value
as zero.

Question 31

what is the technique for logarthmic

Answer 31

–> When comparing rate of changes,
important to use percentage and
logarithm scale
–> equal rate of change appear as equal slope

Question 32

what is the technique of overlapping

Answer 32

It is easier to detect cyclical
patterns by overlapping the
multiple cycles on the same chart

Question 33

what is the technique of stacking

Answer 33

If there is a need to compare multiple variables in the same time period but they are expressed using different units of measure, stacking line charts can be used.