# STAT*2060 Final Exam Notes - Saturday, November 29, 2014...

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Saturday, November 29, 2014STAT*2060 Final Exam1. IntroductionStatistics- science of collection, classifying, summarizing, analyzing and interpretingdataDescriptive Statistics- numerical and graphical methods used to analyze, interpretand represent dataInferential Statistics- use information from a sample to make generalizations about apopulationQuantitative Data -numerical data that can be measureduse histograms, box plots and stem & leaf plotsDiscrete Data -measurements can only take specific valuesex. number of rooms in a residenceContinuous Data -measurements can take any value within a specific rangeex. height, weight, timeOthers include:Ordinal, Interval, Ratio dataQualitative Data -can not be measured on a numerical scale and data falls intocategoriesex. Favourite flavour of ice creamuse bar charts and pie charts to plot informationObservational Studies -we observe units and take measurements without assigningtreatmentsExperimental Studies -treatments are assigned to units and then the effects areobserved and measuresPopulation -large group of units that we are interested in studyingSample -a subset of the populationParameter -numerical characteristic of a population (usually not known)Statistic (estimator) -numerical characteristic of a sample (known)1
Saturday, November 29, 2014Statistical Inference -to calculate estimators of population parameters, and to quantifythe accuracy of these estimators with probabilitiesBiased SamplingSelection Bias -sample is not representative of the population because a subsetof the population has no chance of being selected for the sampleNon Response Bias -there may be a reason that certain respondents refuse toparticipateMeasurement Error -the response measured and recorded for an individual unitis not correctRandom Sample -each unit in a population has an equal chance of being selected2. Descriptive StatisticsSample Variance and Sample Standard Deviationmeasures of spread relative to the meanSD is used more often when describing data because variance the units are squarednon negative (greater than or equal to zero)Histogramsgraphical way to represent (quan) datawe make class intervals (equal/varying width) which contains data of interestcount the frequency at which we observe data falling into one of these classintervals and construct a frequency tableRelative Frequency = frequency (height)/midpoint of intervalSkewnessmeasure of how much a distribution leans towards a particular side or whether it issymmetricSymmetric- observations cantered around mean and tail of evenly on both sidesRight (Positively) Skewed- tail to the right side of the mean and more observationsconcentrated on smaller values2
Saturday, November 29, 2014mean > medianLeft (negatively) Skewed- tail to the left side of the mean with more observationsconcentrated on larger valuesmean < medianQuartilesFirst Quartile (Q1) - 25% of observations lie below this value (25th percentile)

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