Chapter 3

Question 1

Techniques for dealing with uncertainty

Answer 1

Set minimum payback period
increase discount rate to submit project to higher hurdle rate
make prudent estimates of outcomes to assess worst situation
assess worst and bestt case
use sensitivity analyssi

Question 2

Sensitivity formula

Answer 2

NPV Project / NPV of CF subject to uncertainty

Question 3

Strength of sensitivity analysis

Answer 3

Information presented in form which facilitates subjective judgement

identifies areas of success critical to project

Question 4

Critical issues strengths

Answer 4

Identifies areas which are critical to the success of project, if undertaken these can be carefully monitored

Question 5

Sensitivity issues - independence

Answer 5

Assumes changes to variables can be made independently

Question 6

Sensitivity analysis - probability

Answer 6

Only identifies how far a variable needs to change, not the likelihood that it will change

Question 7

Sensitivity analysis - no answer

Answer 7

Not optimising technique, only gives information and does not point to decision

Question 8

Linear regression - predict the

Answer 8

Dependent variable

Question 9

Linear regression - factors that are thought to impact on dependent variable are called

Answer 9

independent variable

Question 10

Advantages of linear regression

Answer 10

Simple to use and easy to explain
Can be used to predict impact beyond current estimates

Question 11

Limitations of linear regression

Answer 11

There is not always a linear relationship
basic models only consider one variable at a time
May identify spurious relationships, correlation is not causation
less meaningful if the data is inaccurate

Question 12

Advantages of decision trees

Answer 12

Simple ones easy to explain and logical
Can be used to consider different outcomes that can occur based on changes in a number of variables
consider multiple decisions

Question 13

Limitations of decision trees

Answer 13

Usually restricted to small number of outcomes
large decision trees can be hard to interpret

Question 14

Advantages of simulation

Answer 14

Gives more info about possible outcomes and probabilities
useful for problems which cannot be solved analytically

Question 15

Limitations of simulation

Answer 15

Not a technique for making decision, only gives info
can be time consuming without a computer
can be expensive to design and run for complex project
Monte Carlo techniques require assumptions about probability distributions and reltaionships between variables

Question 16

Advantages of prescriptive analysis

Answer 16

Capability to identify optimum investment decisions whilst considering impact of multiple decisions and variables

Question 17

Limitations of prescriptive analysis

Answer 17

Creating reliable prescriptive models is complex and requires specialist skills
reliability depends on reliability of data used and ability to predict future outcomes from past data

Question 18

Reasons data analysis is not always accurate

Answer 18

Inherent bias in the data (intentional/unintentional)
Data may have been intentionally manipulated
Data may have been analysed accurately, but presentation of the data or conclusions may be flawed

Question 19

Data bias definition

Answer 19

not representative of the population

Question 20

Selection bias definition

Answer 20

Data is not selected randomly and not representative of the population as not every item has equal chance of being selected

Question 21

Self selection bias definition

Answer 21

Occurs when individuals elect themselves to be part of a sample (online questionnaire)

Question 22

Observer bias definition

Answer 22

Occurs when observing and recording, researcher allows assumptions to influence observations

Question 23

Omitted variable bias definition

Answer 23

Key variables are not included within the data to be analysed

Question 24

Cognitive bias definition

Answer 24

Relates to human perception and includes bias depending on how data is presented

Question 25

Confirmation bias definition

Answer 25

When people see data that confirms their beliefs and ignore data that disagrees

Question 26

Survivorship bias definition

Answer 26

Sample only contains items that survived some previous event

Question 27

Mean definition

Answer 27

Average- sum of all values divided by number

Question 28

Standard deviation

Answer 28

Show amount of variability in a data set, showing on average how far each result lies from the mean
risk means variablility of outcomes and can be measured using SD

Question 29

Coefficient of variation

Answer 29

Ratio of SD to mean
SD/Mean * 100

Question 30

Normal distribution

Answer 30

Frequency distribution arises frequently in ‘real life’ any distribution that is symmetrical around the mean

Question 31

% of data within 1SD above/below mean

Answer 31

68%

Question 32

% of data within 2 SD above/below mean

Answer 32

95.4%

Question 33

% of data within 3 SD above/below mean

Answer 33

99.7%

Question 34

Left/negatively skewed distribution has the majority of values concentrated on

Answer 34

RHS of distribution

Question 35

Right/positive skewed distribution has majority of values concentrated on

Answer 35

LHS of distribution

Question 36

Left skewed data median mode mean order (left to right)

Answer 36

Mean Median Mode

Question 37

Right skewed data median mode mean order (Left to right)

Answer 37

Mode, median, mean

Question 38

Advantages of expected values

Answer 38

Information reduced to single number for each option
Idea of average is understood

Question 39

Limitations of expected values

Answer 39

Probabilities may be difficult to estimate (could base on past experience or market research)
expected value may not correspond to any expected outcome
unless the same decision has to be made many times, expected value will not be achieved, is therefore not valid way of making decision in one off situation
gives no indication of spread