Employment SkillsLecture week 9

Business modellingAnalysing data: a brief tour of some useful concepts

Presentation skills

Working with scales

• Scales show how concepts differ. • The four widely accepted levels of measurement called

“measurement scales” are: 1.Nominal2.Ordinal3.Interval4.Ratio

1. Nominal Scale

• Naming different items• Eg:-Religious Groups, smoking v/s non smoking, male or female, yes or no

• No order is implied• No quantifiable value• Identifying a number of categories• Since nominal data is simply categorical, only few statistical test can

be performed• Often presented in bar or pie chart• Mode

2. Ordinal Scale

• Items can be ranked• Intervals between items not equal• Might not have precise values• Example:-

• Child, adolescent, adult• 1= small, 2= medium, 3= large• Ranking of favourite sports

• Ordinal scale are often used to measure attitude and perception• For e.g. how satisfied the customer are? Not satisfied and satisfied• Nurse asking for pain level of patient

• Statistical tests: all nominal tests plus median

3. Interval Scale

• Data is ranked according to equal intervals• There is no zero point• Example:-IQ score• Statistical tools: mean, median, mode, standard deviation• Impossible to multiply or divide

IQ Score

Intelligence Interval Cognitive Designation40 -54 Severely challenged (Less than 1% of test takers)55 -69 Challenged (2.3% of test takers)70 -84 Below average85 -114 Average (68% of test takers)115 -129 Above average130 -144 Gifted (2.3% of test takers)145 -159 Genius (Less than 1% of test takers)160 -175 Extraordinary genius

4. Ratio Scale

• Allows data to be ranked with precise quantifiable intervals and a zero point

• Example:- weight, time• All statistical tests can be performed• Can make comparisons: an 8 kg baby is twice as heavy as a 4 kg baby

Level of measurement decision tree

Ordered?No.

Nominal

No.Ordinal

No.Interval

Yes. RatioYes. Zero means

none?Yes. Equally

spaced?

Summarising data

• Collecting data on how students travel to SchoolSample size = 44

Mode of Transportation Number of students

Walk 12

Cycle 15

Motorcycle 9

Car 3

Bus 5

Summarising data

• Percentage Calculation• Sample size = 44

Mode of transportation Number of students Percentage

Walk 12 24%

Cycle 15 30%

Motorcycle 9 18%

Car 3 10%

Bus 5 18%

Could draw block diagram

walk cycle motorcycle car bus0

5

10

15

20

25

30

35

mode of transportation used by students

mode of transportation used by students

Could draw pie chart

students mode of transportation

walk cycle motorcycle car bus

Quantitative Forecasting Methods

Causal

Models

Quantitative Forecasting MethodsQuantitative Forecasting Methods

Quantitative

Forecasting

Time Series

Models

RegressionExponential

Smoothing

Trend

Models

Moving

Average

Time Series-The art of forecasting

• Set of evenly spaced numerical data• Obtained by observing response variable at regular time periods

• Forecast based only on past values• Assumes that factors influencing past, present, & future will continue

• ExampleYear: 2007 2008 2009 2010 2011Sales: 78.7 63.5 89.7 93.2 92.1

Time Series ComponentsTime Series Components

Trend

Seasonal

Cyclical

Irregular

Trend ComponentTrend Component• Persistent, overall upward or downward pattern• Due to population, technology etc.• Several years duration

Mo., Qtr., Yr.

Response

© 1984-1994 T/Maker Co.

Trend Component

• Overall Upward or Downward Movement• Data Taken Over a Period of Years

Sales

Time

Upward trend

Cyclical ComponentCyclical Component• Repeating up & down movements• Due to interactions of factors influencing economy• Usually 2-10 years duration

Mo., Qtr., Yr.

Response

Cycle

Cyclical Component• Upward or Downward Swings• May Vary in Length• Usually Lasts 2 - 10 Years

Sales

Time

Cycle

Seasonal ComponentSeasonal Component• Regular pattern of up & down fluctuations• Due to weather, customs etc.• Occurs within one year

Mo., Qtr.

Response

Summer

© 1984-1994 T/Maker Co.

Seasonal Component• Upward or Downward Swings• Regular Patterns• Observed Within One Year

Sales

Time (Monthly or Quarterly)

Winter

Irregular ComponentIrregular Component• Erratic, unsystematic, ‘residual’ fluctuations• Due to random variation or unforeseen events

• Union strike• War

• Short duration & nonrepeating

© 1984-1994 T/Maker Co.

Quantity variables

• Examine the pulse rates of members of staff

89 68 92 74 76 65 77 83 75 87 85 64 79 77 96 8070 85 80 80 82 81 86 71

90 87 71 72 62 78 77 90 83 81 73 80 78 81 81 75

82 88 79 79 94 82 66 78 74 72

Quantity variables

• Examine the pulse rates of members of staff• is there a pattern?• what is the minimum value?• what is the maximum value?• what is the spread between minimum and maximum?• are some pulse rates more common?

Quantity variables

• Better to sort the data into numerical order62 64 66 68 70 71 72 7273 74 76 77 78 78 80 8081 81 82 83 90 87 90 6571 74 77 79 80 81 83 8792 75 77 79 80 82 85 8894 72 75 78 79 81 82 8589 96

Distribution

• Now we have a distribution

• easy to see the minimum• easy to see the maximum• difference between maximum and minimum = range• range here is 96 – 62 = 34

Distribution

• Draw a histogram to show how many in each group• 60 –64 2• 65 –69 3• 70 –74 8• 75 –79 12• 80 -84 13• 85 –89 7• 90 –94 4• 95 –99 1

Distribution

60-64 65-69 70-74 75-79 80-84 85-89 90-94 95-990

2

4

6

8

10

12

14

Column1

Column1

Different type of ‘Average’

Mean

• Mean:

• The mean is the Average of a group of numbers.• To find the Mean, first you must add up all of the numbers.• And then divide the sum by number of observations

Mean Example

12, 15, 11, 11, 7, 13First, find the sum of the data.

12+ 15 + 11+ 11+ 7 + 13 = 69

Then divide by the number of data69/ 6- 11.5

Therefore, the mean is 11.5

Question:

• what is the mean of this distribution?• Data: 62, 70, 73, 76, 78, 80, 81, 82, 86

• there will be some above and some below the mean• unless all the values are the same

Median

• The median is the middle most value when the numbers are arranged in numerical order. (Ascending or descending)

Median example

• First, let’s examine these five test scores.• 78 93 86 97 79

• We need to put them in order.• 78 79 86 93 97

• The number in the middle is 86• 78 79 86 93 97

• In this case, the Median is 86!

12, 15, 11, 11, 7, 13• First, arrange the data in numerical order.

7, 11, 11, 12, 13, 15

• Then find the number in the middle or the average of the two numbers in the middle.

11 + 12 = 23 23 / 2 = 11.5

The median is 11.5

• An electronics store sells CD players at the following prices: • $ 350, $ 275, $500, $325, $100, $375, and £300.• What is the median price?

Mode

• The mode refers to the number that occurs most frequently• It’s easy to remember…the first two letters are the same!• MOde and MOst frequently

Mode Example

12, 15, 11, 11, 7, 13

The mode is 11

Mode Example

• Here is an list of temperatures for one week.Mon. Tues. Wed. Thurs. Fri. Sat. Sun. 17° 19° 13° 17° 23° 17° 12°

Again, We will put them in order.12° 13° 17° 17° 17° 19° 23°

• 17°is the most frequent number, so the mode= 17°

• Sometimes a set of data will have more than one mode.

• For example, in the following set the numbers both the numbers 5 and 7 appear twice.

2, 9, 5, 7, 8, 6, 4, 7, 5

• 5 and 7 are both the mode and this set is said to be bimodal.

• Sometimes there is no mode in a set of data.

3, 8, 7, 6, 12, 11, 2, 1

• All the numbers in this set occur only once therefore there is no mode in this set.

Range:

• The range of a set of data is the difference between the largest and the smallest number in the set.

Range Example

• The range of a set of data is the difference between the largest and the smallest number in the set

• .For example, consider the following set:40, 30, 43, 48, 26, 50, 55, 40, 34, 42, 47, and 50

To find the range you would take the largest number, 50, and subtract the smallest number,

26.55 –26 = 29The range is 29!

• Mean The average

• Median The number or average of the numbers in the middle

• Mode The number that occurs most

Hypothesis

Hypothesis

• A hypothesis is a proposition–a tentative assumption which a researcher wants to test for its logical and empirical consequences.

• E.g. :-• American cities are experiencing budget difficulties

• An increase in the family income leads to an increase in the percentage of income saved.

Types of Hypothesis

• Null Hypothesis (H0)• Statistical hypothesis which is started with a view of testing or verifying its

validity• These are hypothetical statements denying what are explicitly indicated in

working hypotheses.• E.g. Even though there is a relationship between a family income and

expenditure on recreation, a null hypothesis may state: “There is no relationship between families income level and expenditure on recreation”.

• Alternate Hypothesis (H1)• Alternate of Null hypothesis

Type I & Type II errors

• Type I error: Rejecting the null hypothesis, when it is true• Type II error: Accepting the null hypothesis, when it is false

Decision Ho. True H1. False

Accept Correct decision Error

Reject Error Correct decision

Dealing with errors

• Suppose we intend to cross a busy main road• decide not to cross; there is traffic coming -correct decision• decide to cross; there is no traffic coming -correct decision• decide not to cross; there is no traffic coming

• type II error -no danger, but wasted time• decide to cross; there is traffic coming

• type I error -danger-risk of injury

Correlation

Correlation

• Samples can be said to be correlated if they demonstrate some pattern

• there may be:• positive correlation• negative correlation• No correlation

Positive correlation

• An increase in one variable is associated with an increase in the other

Negative Correlation

• An increase in one variable is associated with a decrease in the other

Example for Correlation

• Suppose the variables are:• sales of hot water bottles• average temperature

• Do higher HWB sales cause lower temperatures?• Do lower temperatures cause higher HWB sales?• Is there some other common cause?• Is there cause and effect?• Can we use one to predict the other?

No Correlation

• No pattern emerges• No connection seen between a change in one variable and the other• No cause and effect relationship

Linear Programming

Linear Programming

• Optimising within constraints• Balance time, skill and resources within limitations

Example: what is the optimum balance bowls/plates?

• Plates –make £2 profit• Bowls –make £5 profit

Linear Programming

• Constraints:• Maximum number made each week:

• Plates = 150• Bowls = 120• Raw materials –enough for 200 bowls/plates per week• Cannot make a negative number of bowls/plates!

Linear Programming

• Specify equations and inequalities:Plates• Number of plates = X

X <= 150 and X >= 0Bowls• Number of bowls = Y

Y <= 120 and Y >= 0Raw materials

X + Y <= 200

Linear Programming

Linear Programming

• Taking values from the graph:• Revenue= 2X + 5Y

= 2(80) + 5(120)= 160 + 600= £760

• This is the optimum balance: 80 plates and 120 bowls• We cannot make any more bowls (120 maximum)• We are within the constraint of raw materials (200 maximum)

PRESENTATION SKILLS

• It’s just talking, isn’t it?

What is a presentation?

What is presentation?

• Formal talk of set length• On a set topic• Given to a set audience• Appropriate audio/visual aids and supporting materials to connect

with actual audience

• It’s all an act

What is a presentation?

What is presentation? - Act

• Presentation is performance• To make it work, act happy, confident and interested even you are

bored to death.

Its an act- positive body language

• Face the audience• Do not look the board behind you• Do stand or sit straight• Do not hold anything in front of your face• Do smile• Do draw people into your presentation with brief welcoming gestures.

Its an act- body language (contd..)

• Do stand in relaxed manner• Do not stand there with clenched fist• Do not act as if you want to be somewhere else• Do not act as if you hate everybody else on the team• Do act calm, confident and in control

• It’s communication

What is a presentation?

It’s a communication (contd..)

• Create a relationship with audience• Communicate and interact with them• Make eye contact with everybody in audience to draw them into your

talk and take them with you.• Act like an actor on stage- never ever speak from script

• The formal conventiono Introduction and Agenda ( tells the audience what is coming in the whole presentation)o Body (is the presentation and presents in formation in logical structure). One idea at a

timeo Argument, evidence, discussion, point, audio visual aids.

o Conclusion ( revisit arguments, restate points, thank people for listening, ask for questions)

o Questions and Answer (take questions, answer briefly, thank again)

What is a presentation?

Formal convention- introduction

• Have an introduction with clear agenda.• Introduce yourself• Give the topic title• Make opening remarks• Give the agenda of talk

Formal convention- the body

• Answer the question that you were set• Think about one big idea at a time• Support your idea by argument and evidence and AVA• Think about building a logical case

The formal convention- The conclusion• Draw the whole presentation together• Revisit you main arguments• Restate the main points

The formal convention- the question and answer session• Don’t rush out after the presentation is over• Thank the audience for listening• Ask them if they have any queries

• P1 – Plan• Time limit - how can you fit the topic into the time you have been allowed?

What will you have to put in and what will you have to leave out?

• Topic and audience - Remember, an audience is made up of real people with real knowledge and expectations of their own.

How to succeed in presentations –4 Ps

• P2 – Prepare

How to succeed in presentations –4 Ps

P2- Prepare

• Remember to brainstorm the topic, link to the learning outcomes, follow your action plan

• Read actively and interactively• Remember to make your AVA with back ups e.g. handouts of

presentation• Review your notes• Review your AVA- which will you use and which you wont

P2- prepare (contd..)

• Plan the body of presentation• Remember to convince yourself• Prepare a script• Prepare key words, key examples, key names and dates to guide you

through the presentation

• P3 – Practise: rehearse,rehearse,rehearse• Refine and polish• Learn the presentation• Give it life

How to succeed in presentations –4 Ps

• P4 – Present

How to succeed in presentations –4 Ps

SWOTting your presentation

• Review and evaluate your own presentation• Because of emotional dimension of presentations, undertake this in

two stages• Immediately after presentation, tell yourself what a wonderful presentation

it was.• After some time, undertake detailed SWOT analysis of your presentation

Effective power-point presentation

Big

Clear

Consistent

Simple

Factors for effective PPT

Effective power-point presentation

Effective power-point presentation

Effective power-point presentation

Any Questions?