business research session 11 data analysis

8/14/2019 Business Research Session 11 Data Analysis

1/21

Session 11

Data Analysis and Presentation


2/21

Prior to analysis

Field and in house editing for consistency

and completeness

Coding of free response questions

Behavioural and segmenting data (SPSS)

Method of entry into computer

Descriptive and cross tabulation data Analysis by difference / Quadrant analysis

/ Perceptual mapping / Bakers box


3/21

Forms of Analysis

Normally analysis is question drivenwhat information is required to answer aspecific question

Two broad main types of analysis:

Analysis of difference

Analysis of relationships / causation


4/21

Hypothesis testing

The null and alternative hypothesis

Significance level is crucial. Could thedifference observed be due to chance, orcan we be at least 95% sure that it is dueto the phenomenon being tested.

Sample size is also critical in assuring thelevel of confidence and error which mightbe anticipated.


5/21

Exercise: Are IIS students more

satisfied than those at Ram?

The hypothesis is that IIS students are

more satisfied than students at RAMoverall.

Average rating for students overall at Ramis 3.6 For IIS it is 3.9, based on a sampleof 100, with an SD of 1.5

Two tailed test (0.025% either end, Z =1.96)


6/21

Chi Squared Test

A test for significance in the analysis of

frequency distributions

Based on the difference betweenobserved and expected results if therewas no difference

Can be used for both ordinal and nominaldata sets

Easiest and most widely used test!


7/21

Exercise: Boys are better than girls!

Out of the 99 students who took the MBA

Interim examination in Business ResearchMethods, 14 of the 33 men present scored

less than 30 marks, and overall 33 peoplescored below 30.

Is there a significant difference in

performance between the men andwomen?


8/21

Other methods of testing between

groups

t-test, used to calculate differences

between means

Z test for comparing proportions

Analysis of variance (ANOVA)

F test / F ratio

(See Zikmund: Pages 521 534)


9/21

Measures of Association

Association: Where one variable correlates withanother

Co-variance: Where two variables are

associated together, but both are associatedwith a third (undefined) variable

Coefficient of determination: A measure of theexplanation of one variable by another. It is thesquare of the correlation coefficient and is thebasis of factor analysis


10/21


11/21

Regression

Linked to association, but regression seeks tocreate a formula to explain the association.

Two forms; straight line (y = mx + c) or non

linear of several forms Regression line plotted by least squares and is

the line of best fit

Used extensively in sales forecasting, butignores the point of inflexion problem seen alsoin extrapolation


12/21

Bakers Box: An example of best

fit regression line

I Dont

Believe

IT

Value

Added

The GoldenTriangle

Avis

Country

Cheap AndNasty

Cheap AndCheerful

ITS A

Rip Off

You MustBe Joking

Low Quality

High QualityLine Of

Expectation

High

Price

Low

Price

Gullibility

Credibility


13/21

Exercise: Expansion at Rotiboy!

Rotiboy have established that the sales for anoutlet of their business (y) can be defined by thenumber of people living within one mile of the

outlet (x) by the line y = 20 + 0.55x, where boththe constant is denominated in 000 baht, and x

as 000 population.

On the basis of this data what is the likely

weekly revenue (in baht 000) for an outletestablished where there is a local population of10,000


14/21

Multivariate Analysis

Multivariate regression analysis ( TheFishbein model of attitude measurement)

Multivariate Analysis of Variance

(MANOVA) Factor analysis: Reduction of complex

variables into smaller number of factors

Cluster analysis CHAID (Chi squared automatic interaction

detection)


15/21

Tesco and the use of AID

Based on customer data collected at POS

Analysed by AID to establish levels ofproduct penetration and specific customercharacteristics

Can isolate groups as small as 5,000 froma population of 26 million!

Visit www.dunnhumby.co.uk


16/21

Communicating Research

The communicator

The message

The medium The Audience

Feedback


17/21

Oral communication

Stand up, speak up, and shut up. There isa limit to peoples concentration

Graphics need to be simple (not more than

12 figures on a slide). More than thishighlight

Be aware of your personal body language

If you use technology, make sure it works! Have clear objectives as to what to put

over


18/21

Some tips on oral presentations

Variety; in voice, tone, movement, bodylanguage, all elements of posture, etc. Suit yourbody language to the message

Be sure you can get away with humour. Be verycareful if you use it with an internationalaudience as it is very cultural!

Look at your audience, good eye contact

Do not distribute report beforehand if you wantto be selective in how you take from it.

Leave time at the end for questions


19/21

Presenting statistical results

Never assume the audience knows as muchabout statistics as you do!

Dont try and blind them with statistics

Remember there are lies, dam lies, andstatistics Many are very cynical of them!

Use statistics to demonstrate data in terms of its

use in making a decision. Applied statisticsrather than statistics for their own sake!

Explain what they mean!


20/21

Written reports

Length and level of reading are inversely related Always provide an annotated executive

summary with guideposts to deeperexplanations as required.

Make sure the report provides the informationrequired in order to come to the decisionrequired

Use tables, graphs and charts as appropriate to

illustrate data and make points. Remember a multicoloured pie chart loses a lot

in black and white!


21/21

Specialist AnalyticalTechniques

CHAID (Chi Squared Automatic Interaction

Detection)

ACORN / TGI Retail Location

Market Penetration Analysis

Sensitivity Analysis

Resource Allocation

business research session 11 data analysis

Documents