9 - Predictive Analytics

Question 1

Long-term forecasts

Answer 1

Question 2

Medium-term forecasts

Answer 2

Question 3

Short-term forecasts

Answer 3

Question 4

Qualitative forecasting methods

Answer 4

Question 5

Management judgement

Answer 5

Question 6

Delphi method

Answer 6

Question 7

Market research

Answer 7

Question 8

Features of the main qualitative methods

Answer 8

Question 9

Quantitative forecasting methods

Answer 9

Question 10

Density index and Classification of time series

Answer 10

Question 11

Regular time series decomposition

Answer 11

Question 12

Trend

Regular time series decomposition

Answer 12

Long-term modification of data patterns over time

It may depend on changes in population and on the product (or service) life cycle

Question 13

Cyclical variation

Regular time series decomposition

Answer 13

Caused by the “business cycle”, which depends on macro-economic issues

Quite irregular, but its pattern is roughly periodic

Question 14

Seasonal variation

Regular time series decomposition

Answer 14

Question 15

Residual variation

Regular time series decomposition

Answer 15

Portion of the data pattern that cannot be interpreted as trend, cyclical or seasonal variation

Result of numerous causes, each of which has a small impact

Question 16

Forecasting process

Answer 16

Question 17

Data preprocessing

Answer 17

Question 18

Insertion of missing data (imputation)

Algorithm and Example

Answer 18

Question 19

Outliers

General Information and Algorithm

Answer 19

Question 20

Outliers

Example

Answer 20

Question 21

Data aggregation

General and Algorithm

Answer 21

Question 22

Data aggregation

2 Example

Answer 22

Question 23

Removing the calendar variations

General and Algorithm

Answer 23

Question 24

Removing the calendar variations

Example

Answer 24

Question 25

Deflating monetary time series

General information and Algorithm

Answer 25

Question 26

Deflating monetary time series

Example

Answer 26

Question 27

Adjusting for population variations

Algorithm

Answer 27

Question 28

Adjusting for population variations

Example

Answer 28

Question 29

Normalizing the data

Algorithm

Answer 29

Question 30

Normalizing the data

Example

Answer 30

Question 31

Notation

Choice of the forecasting method

Answer 31

Question 32

Casual methods

Choice of the forecasting method

Answer 32

Question 33

Elementary technique

Constant trend

Answer 33

Question 34

Simple moving average method

Constant trend

Answer 34

Question 35

Weighted moving average method

Constant trend

Answer 35

Question 36

Exponential smoothing method (or Brown method)

Constant trend

Answer 36

Question 37

Exponential smoothing method (or Brown method) Example

Constant trend

Answer 37

Question 38

Forecasts for subsequent time periods

Constant trend

Answer 38

Question 39

Elementary technique

Linear trend

Answer 39

Question 40

Holt method

Linear trend

Answer 40

Question 41

Elementary technique

Seasonal variations with periodicity M

Answer 41

Question 42

Winters method

Seasonal variations with periodicity M

Answer 42

Question 43

Winters method Example

Seasonal variations with periodicity M

Answer 43

Question 44

Accuracy measures

Answer 44

Question 45

Accuracy measures

Example

Answer 45

Question 46

Tuning of the forecasting methods

Answer 46

Question 47

Tuning of the forecasting methods Example

Answer 47

Question 48

Forecast control

Answer 48

Question 49

Forecast control Example

Answer 49