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Final Exam Time and Place:. Saturday, Dec 8, 9:00am - 12:00pm EN 1054. Chapter 19.1 Exploratory Data Analysis. What is Exploratory Data Analysis?. An approach to analyze data sets to: Discover patterns Find a better model It’s an iterative process Refine to uncover patterns.

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Final exam time and place

Final Exam Time and Place:

Saturday, Dec 8,

9:00am - 12:00pm

EN 1054


Chapter 19 1 exploratory data analysis

Chapter 19.1 Exploratory Data Analysis


What is exploratory data analysis

What is Exploratory Data Analysis?

  • An approach to analyze data sets to:

    • Discover patterns

    • Find a better model

  • It’s an iterative process

    • Refine to uncover patterns


Confirmatory vs exploratory

Confirmatory vs. Exploratory

Confirmatory analysis

Exploratory analysis

What is the appropriate model?

What is data telling us?

What is structure of model?

Batch of data

Repeated use of a batch .

Iterative search for pattern

Explained variance = ?

Best model

Residuals show pattern?

Factor analysis

  • What decision can be made?

  • How certain can we be?

  • What are values of parameters?

  • Sample

  • ONE use of a sample (data-grinding, otherwise)

  • Single analysis

  • p-value = ?

  • Yes/no decision

  • Residuals acceptable?

  • Experimental design


Exploratory what is the appropriate model

ExploratoryWhat is the appropriate model?

But remember,

pattern ≠ cause


Confirmatory what decision can be made

ConfirmatoryWhat decision can be made?


Inference

Inference

  • Confirmatory

    • Narrow form of inference

    • Relate one Q to another Q (e.g. βreg)

  • Exploratory

    • Broader form of inference

    • Trying to discover a pattern worth running through a confirmatory analysis

P corm P soil

N corn~ N soil

C corn C soil

⁞ ⁞


Don t confuse confirmatory and exploratory analyses

Don’t confuse confirmatory and exploratory analyses

  • Refining models using p-values ≠ exploratory analysis

  • Repeated analysis of the same data set is data dredging (aka: data grinding, data mining, data fishing, data snooping…)

  • Any data set has a degree of randomness, so multiple comparisons may be bound to find a false association


Characteristics of exploratory analyses

Characteristics of Exploratory Analyses

  • Relies strongly on graphical analyses

http://gallery.r-enthusiasts.com/thumbs.php


Characteristics of exploratory analyses1

Characteristics of Exploratory Analyses

  • Simplify – determine best model for pattern


Execution

Execution

  • Define all quantities that are used

    • Procedure statement

    • Name and Symbol

    • Values with Units

  • Identify response and explanatory variables

  • Decide whether to undertake exploratory or confirmatory analysis, stating reasons for choice

  • State screening criterion to distinguish exploratory from confirmatory analysis

    • Visual screening

    • P-value based (e.g. keep if <0.1)


Box and arrow diagrams logic

Box and Arrow Diagrams  Logic

  • Gordon Riley is interested in aquatic productivity of Georges Bank

Light

Nutrients (nitrates, phophates)

Phytoplankton

Zooplankton


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