Chapter 1 usagpan statistics


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Chapter 1 usagpan statistics

  1. 1. Statistical Methods forAnesthesia and Intensive Care1
  2. 2. Required Materials/Resources2Selected Youtube VideosPrimarySupplement tofacilitateunderstanding
  3. 3. Exams• Chapters 1-4• Chapters 5-9• Chapters 10-13• Comprehensive Final3
  4. 4. Type of DataQualitative(Categorical)Type ofCategorizationOnecategoricalvariableGoodness of fitX2TwocategoricalvariablesContingencyTable X2Quantitative(Continous)Type ofQuestionRelationshipsNumber ofPredictorsOneMeasurementContinuousPrimaryInterestDegree ofRelationshipPearsonCorrelationForm ofRelationshipRegressionRanksSpearmans’ rMultipleMultipleRegressionDifferencesNumber ofGroupsTwoRelationbetweenSamplesIndependentTwo Sample t Mann-WhitneyDependentRelated Sample t(paired t tests)WilcoxonMultipleRelationbetweenSamplesIndependentNumber ofIndependentVariablesOneOne WayANOVAsKruskal-WallisMultipleFactorialANOVAsMultivariateAnalysisDependentRepeatedMeasuresFriedman
  5. 5. Chapter 1 – Data Types5
  6. 6. Types of Data• Key Points– Categorical data - nominal and can be counted.– Numerical data may be ordinal, discrete, orcontinuous, and are usually measured.– VAS measurements are ordinal data.6
  7. 7. Types of Data• Qualitative– Data which is descriptiveand characterizes anevent and may includean intangible measure ofworth or quality.7
  8. 8. Types of Data• Quantitative– Data which is measuredvia a numerical scale.8
  9. 9. Types of Data9
  10. 10. Categorical Data• Observations are grouped in categories,counted, and sorted accordingly.• When there are only two categories or choicesthe data is referred to as binary ordichotomous.10
  11. 11. Categorical Data• Examples– Gender• Male• Female– Type of operation• CABG• Hysterectomy• Cholecystectomy• Appendectomy11
  12. 12. Categorical Data• Examples– Type of ICU Admission• Medical• Surgical• Injury• Illness– Adverse/Untoward Event• NPPE• Positioning nerve injury• Transfusion reaction• PONV12
  13. 13. Categorical Data• Reporting– Absolute count– Percentages– Rates– Proportions13
  14. 14. Ordinal Data• Data in which a relative value or ranking canbe applied.– Can be viewed as a hybrid between categoricaland numerical data.– The true measure of the data is not tangible but itdoes have an essence that is more than justdescriptive.14
  15. 15. Ordinal Data• Recording observations– Typical some type of numericalsystem is applied.• Numbers• Roman numerals– Scoring can also be letters orsymbols• A, B, C, D• +, ++, +++, ++++• The advantage of a numericalsystem– Data can undergononparametric statisticalanalysis.• In a nutshell, using a parametricstatistical analysis on ordinaldata.15
  16. 16. Numerical Data• Quantitative Data– Discrete measurments– Continuous measurements• Discrete data– Can only be a wholeinteger• You cannot have half aperson• Continuous data– Can take any value• CBC values• Cardiac Index16
  17. 17. Numerical Data• There can be further division of ContinuousData.– Interval data– Ratio data17
  18. 18. Numerical Data• Interval Data– Location of the zero value is arbitrary and not atrue zero point.• Celsius temperature, Dates• Ratio Data– Simply stated this data has a true zero referencepoint.• Kg, m, in., lb, Kelvin temperature18
  19. 19. Numerical Data• Reporting Numerical Data– Mean– Standard deviation– Median– Range19
  20. 20. A frequent tool used in Anesthesia• VAS– Can measure, pain,PONV, anxiety, patientsatisfaction.– When using the 100 mmscale some researchersuse erroneously thisdata as continuous data.• Is everyone’s pain thesame?20
  21. 21. Ranking of Data TypesRatio Interval Ordinal Nominal21
  22. 22. Ranking of Data Types22
  23. 23. Changing Data Scales• Smoking status can be recorded assmoker/non-smoker (categorical data), heavysmoker/light smoker/ex-smoker/non-smoker(ordinal data), or by the number of cigarettessmoked per day (discrete data).• MI – ischemia or no ischemia, or the extent ofST segment depression in mm.23
  24. 24. Questions on Chapter 1?24