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Final

Final 2017 Notes (got 93% on the test)

13 Pages
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Department
Psychology
Course Code
PSYC 2017
Professor
All

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Description
Chapter 14Descriptive statisticsGoal to describe dataUses it to understand and summarize the key numerical characteristics of the data setInferential statisticsGoal to make inferences about populations from dataYou will learn how to determine if the difference between the experimental and control groupsmeans is statistically significant and if other observed results are statistically significantFrequency distributionsA listing of values in a data set along with their frequencyBar graphCategorical variablesHeight represents frequency of categoryBars do not touchHistogramQuantitative variables continuousNo space between barsLine graphsQuantitative variablesUseful for interpreting interactionsScatterplotsDepicts relationships between two quantitative variablesDependent variable on vertical axis and independent variable on horizontal Measure of central The single numerical value that is considered most typical of the tendencyvalues of a quantitative variable If all the variables were the same there would be no variabilityMeasures of central Most frequently occurring variabletendency modeLeast useful measure of central tendencyMeasures of central Middles scores ascending or descending ordertendency MedianMeasures of central Averagetendency meanMost commonly usedMeasures of central Highest score minus lowest tendency rangeRarely usedMeasures of central Average deviation of the data values from their mean in squared tendency varianceunitsMeasures of central Square root of variancetendency standard Roughly the average amount that individual scores deviate from deviationthe meanAn approx indicator of the average distance that your data values are from their meanMeasures of central Standardized values transformed from raw scores tendency zscoresMean of zdistribution is always zero standard deviation is always 1Indicates how far above or below a raw score is from its mean in standard deviation unitsIn a normal distribution the proportion of scores occurring between any two points can be determined The scores are the values for a variable that have been transformed from their original raw scores into a new standardized metric that has a mean of zero and a standard deviation of 1You can take any set of numbers convert the numbers to z scores and they will always have a mean of zero and a standard deviation of 1 unstandardized difference A comparison of mean differences between levels of a categorical between meansindependent variableThe most direct and simplest way to determine the magnitude of difference between two means is to subtract one mean from another and examine the size of the difference Standardized difference Cohens d is a common measure of effect sizebetween means effect Cohens d is the difference between two means in sizestandard deviation unitsMean difference is divided by standard deviationSmall medium and large effect sizes are indicated by values of at
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