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Professional and Personal Skills

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Suppose you are trying to make an omelette and have placed five good eggs in a bowl. ... 5 egg omelette 1 rotten egg. University of Sunderland ... – PowerPoint PPT presentation

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Title: Professional and Personal Skills


1
Professional and Personal Skills
2
Professionalism and Personal Skills
Facilitation Tools
  • Decision Trees Probability
  • Cause and Effect

3
Learning Outcomes
  • understand basic concepts of probability
  • identify outcomes associated with simple
    decisions
  • construct decision trees for a given problem

4
Probability 1
  • Spin a coin.
  • If you call correctly you receive 5p,
  • if you call incorrectly you lose 5p.
  • There is a 5050 chance (or probability 0.5)
    that you will receive 5p or have to give 5p.

5
Probability 2
  • Spin a coin.
  • If coin comes down heads, you win 10
  • If coin comes down tails, you lose 1
  • If you do not play you receive 1
  • Which would you chose?

6
Probability 3
The outcomes in the previous slide can be
formally expressed in a table. States Alte
rnatives Heads Tails Play 10 -
1 Not Play 1 1 Probability 0.5
0.5
7
Probability 4
  • Imagine a game using 52 standard playing cards.
  • If the cards are cut and the card is red you lose
    2.
  • If the card is black you win 1.
  • If you do not play no money changes hands.
  • States
  • Alternatives Red Black
  • Play - 2 1
  • Not Play 0 0
  • Probability 0.5 0.5
  • Which would you chose?

8
Probability 5
  • In all the previous examples the probability for
    each outcome has been p 0.5 (or 5050)
  • However, your choice will have been influenced by
    both the probability and the seriousness of the
    outcome
  • It is likely that your choice was influenced by
    the amount you might lose or win in a situation
    where the probability remained the same at p 0.5

9
Probability 6
  • A man has a heated driveway to melt snow.
  • He is about to leave home for a weekend and
    learns of an impending storm with an 80 chance
    of snow.
  • Should he turn the heating on?
  • The values of the various outcomes are shown on
    the next slide.
  • when the heat is on the outcome represents
    operating costs,
  • when off he pays 20 to have the driveway cleared.

10
Probability 7
States Alternatives Snow No Snow Heat
on - 8 - 3 Heat off - 20
0 Probability 0.8 0.2 What should
he do? Switch the heating on or leave it
switched off?
11
A Decision Needed
  • Imagine you are a farmer and have a choice of
    crops.
  • The yield of the crops will depend on the
    weather.
  • Suppose your choice was between
  • strawberries,
  • wheat
  • oats
  • the potential yield for each of these crops, in
    s, is on the following slide

12
A Decision Needed
States Alternatives Mild Heavy
Dry Weather Rain Weather Strawberries 28
00 300 100 Wheat 700 400 900 Oats 600 5
00 300 Which would you chose? It obviously
depends on the weather, but you do not know what
the weather is going to be.
13
A Decision
  • Two possible strategies for the previous example
    where the probabilities of different weather
    conditions are are not known are
  • you chose the best of the worst, for each crop
    you identify the worst outcome and chose the crop
    with the highest financial yield
  • in this case wheat in heavy rain
  • you chose the best of the best, for each crop
    you identify the best outcome and chose the crop
    with the highest financial yield
  • in this case strawberries in mild weather.
  • Which would you chose?

14
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15
Decision Trees
  • In the next examples we begin to develop ways of
    combining the decision making process.
  • It involves identifying all the possible outcomes
    for the choices involved, identifying the costs
    and mapping on the probabilities associated with
    each outcome.

16
The Omelette Problem
  • Suppose you are trying to make an omelette and
    have placed five good eggs in a bowl.
  • You are considering adding a sixth egg, as yet
    unbroken.
  • This sixth egg could be good ( G ) or rotten ( R
    ).
  • You may break the egg
  • into the bowl ( B ) which already contains the
    five good eggs,
  • into a saucer ( S ) to test whether it is good or
    bad,
  • or discard it ( D ).

17
The Outcomes
  • The outcomes for B (breaking the egg into the
    bowl)
  • a six egg omelette (the egg is good)
  • a ruined omelette (the egg is rotten)
  • The outcomes for S (testing the egg in a
    saucer)
  • a six egg omelette (the egg is good)
  • a five egg omelette (the egg is rotten)
  • The outcomes for D (discarding the egg)
  • a five egg omelette plus a good egg.
  • a five egg omelette plus a bad egg.

18
Graphical Representation
  • The outcomes for the omelette problem can be
    represented in a chart.

19
Catalytic Converter
Suppose a car manufacturer is to install a
catalytic converter in the exhaust system of its
car. A non destructive leak test can be conducted
on the converter before it is installed in the
exhaust system. However, the test is not perfect
it gives both false positive and false negative
results, that is, fully sealed converters may be
rated as not sealed, while some leaky converters
may be rated as sealed. The manufacturer also has
the option of resealing a converter. It is
guaranteed that the converter will then be
sealed. (Testing costs 2, resealing costs 10.
Every leaky converter will be detected during
final inspection of the assembled car and will
have to be replaced at a cost of 30.
20
Catalytic Converter Decision Tree
21
Decision Tree
A farmer has three crops that could be planted in
a small field. The yield and hence income for
each of the crops will depend on the weather
conditions during the growing period. The
choice of crops is between wheat, oats or
strawberries. The weather conditions can be
predicted as mild, heavy rain or dry. The
probability of mild weather is 0.6, the
probability of heavy rain is 0.35, the
probability of dry weather is 0.05. The
predicted financial yield in pounds for each of
the possible outcomes is set out in the matrix
below together with the probabilities of
occurrence of each of the weather conditions
during the growing period.
22
Choice of Crops
23
Choice of Crops - Decision Tree
24
Cause and Effect Diagrams
  • A technique for identifying possible causes
    affecting a problem.
  • They are sometimes called Fishbone Diagrams
    (because of they have the appearance of the
    skeleton of a fish) or Ishikawa diagrams (after
    their developer Dr. Dr. Kaoru Ishikawa)

25
Cause and Effect Diagrams
  • Are used to
  • define a problem
  • identify data requirements
  • develop objectives for solutions
  • narrow down causes

26
Cause and Effect Diagrams
  • Why Use them?
  • problems often unmanageable
  • in cause and effect analysis they get dealt with
    in small chunks
  • allows us to get ideas down on paper or
    whiteboard or in any written form so that we can
    put our thoughts in order

27
How to Use Cause and Effect Diagrams
  • First identify the problem or effect you want to
    investigate
  • Write the problem in a box on the right hand side
    of a large sheet of paper this is the head of
    the fish then
  • draw a line across the paper horizontally from
    the box, this is the spine, this gives you
    space to develop ideas

28
How to Use Cause and Effect Diagrams
  • Work out the major factors which might contribute
    to the problem
  • draw lines off the spine for each factor and
    label them, these are the bones
  • if you are solving the problem as part of a group
    this may be a good time for brainstorming
  • factors might be, for example, people, systems,
    equipment, materials, external forces and so on.

29
Problem Plus Factors
Factor 1
Factor 2
Factor 3
Factor 4
30
Identify Possible Causes
  • Identify possible causes
  • for each factor identify or brainstorm possible
    causes that may be related to the factor
  • show these as smaller lines coming off the
    bones of the fish
  • where a cause is large or complex, then it may be
    best to break it down into sub-causes
  • show these as lines coming off each cause line.

31
Problem Plus Factors Plus Causes
32
Example stage 1
33
Example stage 2
34
Activity
Factor 1
Factor 2
Factor 3
Factor 4
35
Learning Outcomes
  • understand basic concepts of probability
  • identify outcomes associated with simple
    decisions
  • construct decision trees for a given problem
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