Getting started with regression techniques in SPSS Jarlath Quinn - - PowerPoint PPT Presentation

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Getting started with regression techniques in SPSS Jarlath Quinn - - PowerPoint PPT Presentation

Getting started with regression techniques in SPSS Jarlath Quinn Analytics Consultant Rachel Clinton Business Development www.sv-europe.com A SELECT INTERNATIONAL COMPANY Premium, accredited partner to IBM specialising in the SPSS


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Getting started with regression techniques in SPSS

Jarlath Quinn – Analytics Consultant Rachel Clinton – Business Development

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  • Premium, accredited partner to IBM specialising in the SPSS Advanced

Analytics suite.

  • Team each has 15 to 20 years of experience working in the predictive

analytic space - specifically as senior members of the heritage SPSS team

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  • Overview of regression techniques and linear relationships
  • Performing a simple linear regression
  • Using multiple linear regression to make predictions
  • Predicting response likelihood with logistic regression

Agenda

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  • A family of statistical techniques used to predict outcomes and generate

estimates for hundreds of applications

  • Linear regression is used

– When the outcome is continuous (or scale) data – The relationships between the fields can be described using straight lines

  • Non linear regression

– Is used when the outcome itself is not linear (such as a category) – Often takes the form of logistic regression

What do we mean by ‘Regression’?

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Where are regression techniques used?

  • Modelling the relationship between promotion spend and revenue
  • Estimating pollution levels following heavy rainfall
  • Predicting tourism revenue based on exchange rates and air travel costs
  • Predicting student test scores based on previous test results and peer-group

performance

  • Estimating website hits based on re-tweets and follower numbers
  • Predicting sales of barbeques based on temperature forecasts
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Regression to the mean

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Regression to the mean

*jittered points

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Regression to the mean

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Regression to the mean

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Regression to the mean

}

The regression line is drawn so it that minimises the differences between the points and line itself

( this is called the line of least squares)

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Regression to the mean

* *Anscombe’s Quartet

  • But be careful…
  • It is just an average

after all…

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Measuring linear relationships

0.859 0.434

  • .701

Pearson correlation values

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Non-linear relationships

  • 0.005
  • .671

Pearson correlation values

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Correlations as percentages

  • Correlation = 0.859
  • 0.859 x 0.859 = 0.738
  • 0.738 = 73.8 %
  • Correlation Squared = ‘R Square’

73.8%

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From correlation to prediction

How can we express linear relationships as predictive models?

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How long does it take to cook a chicken?

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How long does it take to cook a chicken?

  • 7 minutes per pound plus 45 minutes
  • 20 minutes per pound plus 20 minutes

y = mx + c

  • r

y = a + bx

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Lets look at a demo of linear regression in IBM SPSS Statistics

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How can we predict category outcomes?

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Logistic regression

  • Allows us to predict things that linear regression can’t
  • Such as…

– Response to a marketing campaign – Credit risk – Whether a subscriber is likely to renew a service – Risk of equipment failure – How likely is it that a particular patient will be readmitted to hospital – Whether a charity donor will switch to direct debit

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Logistic regression

  • But….
  • These outcomes are not continuous numbers so standard linear regression

won’t work

  • When the outcome consists of two categories we use binary logistic

regression

  • When the outcome has three or more categories we use multinomial

logistic regression

  • Logistic gets around the limitations of describing relationships with straight

lines by using a special sigmoid curve

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Logistic regression

00

Discount %

Probability of Responding

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IBM SPSS Regression Module and R integration

  • Using the SPSS Regression Module we can go

beyond Linear Regression and unlock many

  • ther types of Regression functionality
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Exclusive Smart Vision bundle offers

Regression add-on pack

  • If you already have SPSS base and

add the regression module to your licence… – 1 user perpetual licence + 1st year support + 1 day personalised training – £2,900 (+ VAT) – Saving £500 on IBM list price – Offer code SVRegSP001

SPSS & Regression starter pack

  • If you do not have SPSS base licence
  • already. Purchase Base & Regression

– 1 user perpetual licence + 1st year support + 2 days personalised training – £4,229 (+ VAT) – Saving £1,000 on IBM list price – Offer code SVRegSP002

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Working with Smart Vision Europe Ltd

  • As a premier partner we sell the IBM SPSS suite of software to you directly

– We’re agile, responsive and generally easier to deal with

  • As experts in SPSS / analytics / predictive analytics we will

– Deliver classroom training courses – Offer side by side training support – Offer “skills transfer” consulting – Run booster and refresher sessions to get more from your SPSS licences – Give no strings attached advice

  • We are a support providing partner so if you already have SPSS you can source

your technical support directly from us (identical costs to IBM)

– We offer telephone support with real people as well as web tickets / email queries – We offer “how to” support to help you get moving on your project quickly

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Thank you

Contact us: +44 (0)207 786 3568 info@sv-europe.com Twitter: @sveurope Follow us on Linked In Sign up for our Newsletter