Introduction-to-Statistics-and-Quantitative-Research-Methods

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Why square deviations?To calculate variance, the meanof a group of scores issubtracted from each score togive a group of ‘deviations’.• When we take the average ofthe deviation scores, the meanis calculated as the average,and the deviance scores totalzero (positive and negativescores cancel).• If you first square the deviationscores and then add them, youavoid this problem.• The average of these squareddeviation scores is called thevariance.X=individual scoreM=mean of all scoresn= number of scoresExample:80 mean score5 scoresIndividual scores: 90, 90, 70, 70, 80.Sum of (90-80), (90-80), (70-80), (70-80), (80-80)= 0NEED TO SQUARE!(90-80) 2 + (90-80) 2 +(70-80) 2 +(70-80) 2 + (80-80) 2 =100+100+100+100+0=400Variance=100
Variance and StandardDeviation• Variance- hard to interpret because whenthe values are squared, so are the units.• To get back to our original units, you needto take the square root of the variance.• This is the standard deviation.• Standard deviation is a measure of thespread or dispersion of a set of data.• given in the same units as theindicator.• indicates the typical distancebetween the scores of a distributionand the mean.• the higher the standard deviation,the greater the spread of data.S = standard deviationΣ = sum ofX = individual scoreM = mean of all scoresn = sample size(number of scores)Standard Deviation =10
Page 1 and 2: Introduction toStatistics andQuanti
Page 3 and 4: Statistics Defined• Statistics is
Page 6 and 7: Research Methods• Research is str
Page 8 and 9: Research begins when there is aques
Page 10 and 11: Variables• In research, the chara
Page 12 and 13: Types of Variables• Variables can
Page 14 and 15: ExampleA researcher wants to study
Page 16 and 17: 5 minute group exercise1) Researche
Page 18 and 19: Descriptive Statistics DefinedMeanW
Page 20 and 21: MedianA median is the middle of a d
Page 22 and 23: Skewed distributions• Normal dist
Page 26 and 27: Normal Distribution• In a normal
Page 28 and 29: Inferential Statistics• Inferenti
Page 30 and 31: HypothesesNull hypothesis: A hypoth
Page 32 and 33: AlphaAlpha level, or significance l
Page 34 and 35: Beta• Beta is the probability of
Page 36 and 37: Statistical SignificanceWhat is sta
Page 38 and 39: What if there is an effect?• Odds
Page 40 and 41: Power• If findings are statistica
Page 42 and 43: Parametric vs. Non-ParametricSome A
Page 44 and 45: Non-Parametric Tests• Use when al
Page 46 and 47: Types of Analyses• Univariate ana
Page 48 and 49: Types of Analyses• Multivariate a
Page 50 and 51: Basic Research DesignSelecting the
Page 52 and 53: Examples of Tests• T-Test• Allo
Page 54 and 55: Examples of Tests• Correlation•
Page 56 and 57: What have you learned?1) Basic stat
Page 58 and 59: ResourcesGreat resources:• Statis

Introduction-to-Statistics-and-Quantitative-Research-Methods

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