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Introduction to Applied Statistical Analysis

Introduction to Applied Statistical Analysis. A practical course for handling datasets. Statistical analysis. T he science of collecting, exploring and presenting large amounts of data to discover underlying patterns and trends The first step is basic exploratory data analysis

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Introduction to Applied Statistical Analysis

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  1. IntroductiontoAppliedStatisticalAnalysis A practicalcourseforhandlingdatasets

  2. Statisticalanalysis • The science of collecting, exploring and presenting large amounts of data to discover underlying patterns and trends • The firststep is basicexploratorydataanalysis • B.E.D.A. has two main roles: • 1. todefinebasicstatisticalvalues • 2. tovisualizedata

  3. Everydaystatistics (youcanfindotherfactsat http://www.tylervigen.com/)

  4. Softwaresforstatisticalanalysis • Open sourcestatisticalpackages • Public domainstatisticalpackages • Freeware statisticalpackages • Proprietarystatisticalpackages (e.g. OriginPro) • Microsoft Excel is notforthispurpose!

  5. Whywedon’t use Microsoft Excel foranalysis? • Basic functionsand formulas(forgettingaverageanddeviation) • Data visualizationwithgraphs and diagrams • Seemsimpressive (withgraphicalsettings) • Mathematicallyinaccurate (I’ll show you) • Scientificcontentcan be hardlypresentedinsomecases • AnalysisToolPak is needed • This program wasnotdevelopedfordataanalysis

  6. Practice session: objectivesforOrigin • Objective 1. statisticalanalysis, basicplotrepresentations (curve, column, waterfall), linear and nonlinearcurvefitting, BoxPlot • Objective 2. histogram, distributioncurve, scatterplot, Q-Q plot, axisvaluesettings, colourcodemodifications • Objective 3. makingenthalpyprofile, solid vs. dashed line, otheraxisproperties, adding text tograph • Objective 4. datasetconversiontomatrix, matrixrepresentationwithdifferentsurfacetechniques + Graph export topicture (atthe end, foreveryobjectives)

  7. Objective 1 • Statisticalanalysis, basicplotrepresentations (curve, column, waterfall), linear and nonlinearcurvefitting, BoxPlot • Dataset: vibrationalfrequencies of opiorphin (QRFSR), inallits epimers • Forfitting: rotation of Asn

  8. Objective 2 • Histogram, distributioncurve, scatterplot, Q-Q plot, axisvaluesettings, colourcodemodifications • Dataset: potentialenergies (in kcal/mol), radii of gyration and number of H-bondsin opiorphin epimers

  9. Objective 3 • Makingenthalpyprofile, solid vs. dashed line, otheraxisproperties, adding text tograph • Dataset: enthalpies (in kJ/mol) forthereactionsystem of HCN + OH radical

  10. Objective 4 • Datasetconversiontomatrix, matrixrepresentationwithdifferentsurfaces • Dataset: χ1, χ2and ∆rE(inhartree)

  11. ThankYouforYourWork!

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