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# Psych 2017- Ch 7 14 8 Test Three

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Louisiana State University

Psychology

PSYC 2017

All

Fall

Description

Psych 2017Chapter 7 Summarizing and interpreting data using statisticsDescriptive statisticsThe goal of descriptive statistics is to describe sample dataCan be contrasted with inferential statistics where the goal is to make inferences about populations from sample dataFrequency distributionsA listing of values in a data set along with their frequencyGraphic representations of dataBar graph of frequency distributionoUsed with categorical variablesoHeight of bar represents frequency of categoryoBars should not touchHistogramoUsed with continuous quantitative variablesoNo space between barsLine graphsoAlso used with quantitative variablesoParticularly useful for interpreting interactionsScatterplotsoDepicts relationship between two quantitative variablesoCorrelationsMeasures of central tendencyProvides a single value that is typical of the distribution of scoresoModeMost frequently occurring valueLeast useful measure of central tendencyoMedianMiddle score when numbers are in ascending or descending orderoMeanArithmetic averageMost commonly used measure of central tendencyMeasures of variabilityProvides a numerical value indicating the amount of variation in a group of scoresoRangeHighest score minus lowest scoreRarely used as a measure of variabilityoVarianceAverage deviation of the data values from their mean in squared unitsoStandard deviationSquare root of varianceRoughly the average amount that individual scores deviate from the meanoStandard deviation and the normal curveoZscoresStandardized values transformed from raw scoresMean of zdistribution is always zero standard deviation always oneIndicates how far above or below a raw score is from its mean in standard deviation units eg a zscore of 100 indicates a raw score that is one standard deviation unit above the meanIn a normal distribution the proportion of scores occurring between any two points can be determinedExamining relationships among variablesUnstandardized difference between meanoA comparison of mean differences between levels of an independent variableStandardized difference between meansoEffect sizeCohens d is a common measure of effect sizeMean difference is divided by standard deviationSmall medium and large effect sizes are indicated by values of at least 2 5 and 8 respectivelyInferential statisticsHypothesesSignificance testingErrorsHypothesesNull hypothesisoPredicts no effect or relationship in the populationScientific Alternative hypothesisoPredicts an effect or relationship in the populationSignificance testingDetermines the likelihood of obtaining sample data when null hypothesis is trueA decision making process determining if you are dealing with one or two populationsoTwo populations if you reject the null hypothesisoOne population if you fail to reject the null hypothesisHow do you decide to reject the null hypothesisMust base this on analysis of data collectedComparison of group meansoMean arithmetic averageExample people who sleep longer will score higher on a cognitive skills testRandom assignment to two levels of the IVo4 hours or 8 hoursSCAT Sams Cognitive Ability TestoError groups will differ by chance aloneStandard deviation and varianceoBoth measure the variability of scores around the meanStandard deviation is the square root of varianceoIf there is overlap in the scores of the various groups the mean difference in the scores may be due to chanceInferential statistical technique oThese techniques enable you to estimate the probability of the group mean differences occurring by chanceoBy judging the difference between their means relative to the spread or variability of their scores

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