Descriptive Statistics and Inferential Statistics
AgendaData PreparationDescriptive StatisticsInferential Statistics
Data PreparationLogging the Data Checking the Data For AccuracyData Transformations
Descriptive StatisticsUnivariate Analysis Accesses properties of a single variableDistributionCenterSpreadCorrelation Shows ties between variables
Univariate Analysis (distribution)
Univariate Analysis (Center)Mean
Non-stable to extreme observationsVery useful in case of a normal distributionMedian
Great for visual comparison between distributionsVery useful in case of skewed distributionMode
Most frequent value in the distribution
Univariate Analysis (Spread)5 number summaryMin smallest observationQ1 median of the first half of a distributionMedian median of a distributionQ3 median of the second half of a distributionMax biggest observation
1.5 IQR rule
Univariate Analysis (Spread cont.)Standard DeviationShows relation of observations to the mean of a distributionCalculate a distance to mean for each valueSquare the results Divide a sum by the size of a distribution 1 (variance)Take a square root from variance
Univariate Analysis (Spread cont.)Standard DeviationEmpirical ruleapproximately 68% of the scores in the sample fall within one standard deviation of the mean approximately 95% of the scores in the sample fall within two standard deviations of the mean approximately 99% of the scores in the sample fall within three standard deviations of the mean
CorrelationNeed to determine whether there is a relationship between variables
Correlation (cont.)MagnitudeDirection
Correlation (cont.)Calculation
Test significance of produced valueSignificance levelDegree of freedom
Correlation (cont.)Situations when there is only 1 variable in the model are rare in real life. Need to compute correlation matrix.
Inferential StatisticsUsed for drawing conclusion about the population from a sampleEstimationEstimate true value of the parameter from a sampleHypothesis testingDetermine if there is a difference in a parameter value for two groups.
Inferential Statistics (General linear model )General linear model family of statistical models that produce most of inferential statistics
y = b0 + bx + e y outcomeb0 interceptx predictorsb coefficient estimatese error component
Inferential Statistics (General linear model cont.)Foundation for many statistical analysest-testChecks if means of two groups are different from each other on defined confidence levelANOVAChecks if there is a difference between more than two groupsANCOVAAdjusts the use of ANOVA by including covariates into the analysisRegression analysisCreates a model for predicting dependent variable
Inferential Statistics (Dummy variables.)Define different groups.
Research designExperimental Analysis. Quasi-Experimental Analysis.
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