em accessing and assaying prepared data (1)

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1 Accessing and Assaying Prepared Data Introduction Creating a SAS Enterprise Miner Project, Library, and Diagram Defining a Data Source Exploring a Data Source

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Page 1: EM Accessing and Assaying Prepared Data (1)

1

Accessing and Assaying Prepared Data

Introduction

Creating a SAS Enterprise Miner Project, Library, and Diagram

Defining a Data Source

Exploring a Data Source

Page 2: EM Accessing and Assaying Prepared Data (1)

2

Accessing and Assaying Prepared Data

IntroductionIntroduction

Creating a SAS Enterprise Miner Project, Library, and Diagram

Defining a Data Source

Exploring a Data Source

Page 3: EM Accessing and Assaying Prepared Data (1)

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Analysis Element Organization

Projects Librariesand

Diagrams

ProcessFlows

Nodes

...

Page 4: EM Accessing and Assaying Prepared Data (1)

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Analysis Element Organization

Projects Librariesand

Diagrams

ProcessFlows

Nodes

Page 5: EM Accessing and Assaying Prepared Data (1)

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Accessing and Assaying Prepared Data

Introduction

Creating a SAS Enterprise Miner Project, Library, Creating a SAS Enterprise Miner Project, Library, and Diagramand Diagram

Defining a Data Source

Exploring a Data Source

Page 6: EM Accessing and Assaying Prepared Data (1)

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Accessing and Assaying Prepared Data

Introduction

Creating a SAS Enterprise Miner Project, Library, and Diagram

Defining a Data SourceDefining a Data Source

Exploring a Data Source

Page 7: EM Accessing and Assaying Prepared Data (1)

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Defining a Data Source

SASFoundation

ServerLibraries

Select table. Define variable roles. Define measurement

levels. Define table role.

Page 8: EM Accessing and Assaying Prepared Data (1)

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Multiple Choice PollA data source in SAS Enterprise Miner differs from a raw data file because a data source has additional metadata attached. This metadata includes which of the following?

a. the variable roles

b. the variable measurement levels

c. the data table role

d. all of the above

Page 9: EM Accessing and Assaying Prepared Data (1)

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Charity Direct Mail DemonstrationAnalysis goal:

A veterans’ organization seeks continued contributions from lapsing donors. Use lapsing-donor responses from an earlier campaign to predict future lapsing-donor responses.

...

Page 10: EM Accessing and Assaying Prepared Data (1)

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Charity Direct Mail Demonstration

Analysis data: Extracted from previous year's campaign Sample balances response/non-response rate Actual response rate approximately 5%

Analysis goal:

A veterans’ organization seeks continued contributions from lapsing donors. Use lapsing-donor responses from an earlier campaign to predict future lapsing-donor responses.

Page 11: EM Accessing and Assaying Prepared Data (1)

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Accessing and Assaying Prepared Data

Introduction

Creating a SAS Enterprise Miner Project, Library, and Diagram

Defining a Data Source

Exploring a Data SourceExploring a Data Source

Page 12: EM Accessing and Assaying Prepared Data (1)

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Data Access Tools Review Link existing analysis data sets

to SAS Enterprise Miner. Set variable metadata. Explore variable distribution

characteristics.

Remove unwanted cases from analysis data.