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# WSU PSYCH 312 - Frequency Distribution & Descriptive Statistics

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PSYCH 312 1st Edition Lecture 7 Outline of Last Lecture I. MeasurementII. Scales of measurementIII. OrdinalIV. Nominal V. IntervalVI. ratioOutline of Current Lecture I. frequency distributionsa. table b. graphII. measures of central tendency a. mean b. median c. moded. shape of data seti. normal ii. skewed1. negativelyThese notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.2. positivelyIII. graphing dataa. bar graphb. line graph c. examplesCurrent Lecture -Frequency distributionso1st step for getting handle on dataoIndicates how frequently the value appears in setoTable or graphExample of frequency tableShoe size Frequency5.5 16.0 26.5 2oFrequency table can be translated to frequency polygonScores on x axisFrequency of each score on y axis-Measures of central tendency oAdditional info about data provided by descriptive statsMean Mean (X): arithmetic averageTo calculate mean**Things to remember: Sensitive to all scores in setChange in 1 score-->change in meanWill be affected by extreme scoresThe sum of all scores deviations from the mean will equal zeroMedianMedian (Md): middle scoreScore that cuts the distribution into two equal halvesTo find median:Put scores in order of magnitudeIf odd # scores…Take middle scoreIf even # scores..Add two scores on either side of midpoint Divide the sum by 2**things to remember:Not sensitive to each individual scoreNot affected by extreme scores in distributionModeMode (Mo): the most frequent scoreExample scores:Distribution:1, 2, 2, 3, 5, 4, 5, 2, 4, 2Mode= 2NOTE: can be more than one mode in distributionBimodal distibutionNOTE: not all measures of CT are appropriate for all types of dataNominal data Only mode can be usedNot meaningful to talk about median & mean when talking about categorical dataOrdinal dataOnly median & mode can be usedMean is not meaningful because we cant assume that there are equal difference between the values of this particular scaleoMeasures of CT tell us the shape of data setNormal If mean=median=mode-SkewedoPositively Mean>median>modeExtreme scores on right of continuum pull the mean to rightoNegativelyMean<median<modeExtreme scores on left of continuum pull mean to leftoNOTE: better to use median vs. mean for descriptive when a set of scores is heavily skewedMean pulled in direction of skewMedian not affected by extreme scores-Graphing dataoWays to display data graphically asBar graphIV nominalLine graphIV on continuumoEither caseIV on x axisDV on Y axisoEXAMPLE 1: music experiment Plotting mean accuracy of performance in rock, classical & no musical conditionHypothetical resultsRock=25% Classical=50%No music=60%Bar graphUsed b/c IV is NOMINALoEXAMPLE 2: Memory accuracy recall under different doses of same drug (0, 50, 100 mg)Results: (mean accuracy)0 mg dose=25%50 mg dose= 50%100 mg dose= 60%Line graph Used b/c IV lies on a

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