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67 Cards in this Set
 Front
 Back
E.g. nominal scale

sex
eye colour DSM diagnosis religion i.e. unordered categories 

E.g. ordinal scale

likert scale
i.e. categories and rank order 

E.g. interval scale

IQ scores
temperature i.e. rank order and equal intervals can add & subtract 

What type of measurement?
1. religion 2. IQ score 3. DSM diagnosis 4. height 5. gender 6. likert scale 7. reaction time 8. frequency of agressive acts 
1. nominal
2. interval 3. DSM diagnosis 4. interval 5. nominal 6. ordinal 7. ratio 8. ratio 

E.g. ratio scale

# calories consumed
reaction time i.e. rank order, equal intervals AND absolute zero can multiply & divide 

Types of measurement in increasing complexity

N ominal
O rdinal I nterval R atio 

Cumulative frequency

total number observations that fall at or below each score


Kurtosis

the relative peakedness of a distribution
more peaked = leptokurtic more flat = platykurtic 

Skewed distribution

more than half observations fall on one side of distribution
postive = low score negative = high score 

Measure of central tendancy

mode (Mo)
median (Md) mean (M or X) 

Relationship bet measures of central tendency in skewed distributions

positively skewed d:
mean, greater than median, greater then mode negatively skewed d: mode, greater than median, greater than mean 

Measures of variance

range
variance standard deviation 

Def: variance

a measure of variability calculated by dividing the sum of squares
SS / n (population) SS / n1 (sample) 

Def: standard deviation

square root of the variance
a measure of variability of scores around the mean SS / n  then take square root 

Re: Inferential statistics,
What is a sample statistic used for 
to estimate a population parameter


Sampling error

random error responsible for diff bet sample values and population


Sampling distribution of the mean

distribution of means obtained if large number of equalsize random samples are drawn from same population


3 predictions of Central Limit Theorem

1. as sample size increases, sample distribution of mean approaches normal distribution
2. mean of sampling distribution of the mean = population mean 3. SD of sample distribution of the mean = population SD divided by square root of sample size 

Def: Standard error of the mean
What does it measure 
SD of sampling distribution of the mean
variability due to effects of random error 

What happens to standard error when
1. SD larger & sample size smaller 2. SD samller & sample size larger 
1. SE larger
2. SE smaller 

2tailed vs 1tailed hypothesis

2tailed = nondirectional
1tailed = directional 

rejection / critical region

region of unlikely values
lies in one or both tails of sampling distribution values occur as a result of sampling error 

retention region

region of likely values
lies in central portion of sampling distribution 

What happens to hypotheses if sample statistic is in rejection region

null hypothesis is rejected
alternate hypothesis is retained 

What happens to hypotheses if sample statistic is in retention region

null hypothesis is retained
alternate hypothesis is rejected 

Size of rejection region defined by...

alpha
level of significance note: alpha = 0.05 means 5% in rejection region 

Type I error

reject a true null hypothesis


Type II error

retain a false null hypothesis


Statistical "confidence"

certainty about the decision re: null hypothesis


Statistical "power"

ability to reject a false null hypothesis


Parametric tests

evaluate hypotheses about population means, variances etc.
e.g. ttest, ANOVA interval or ratio scale 

nonparametric tests

evaluate hypotheses about shape of distribution
e.g. MannWitney U test, Wilcoxon ordinal or nominal scale 

degrees of freedom

N1 (ttest)
C1 (chisquare) 

What information do you use to select an inferential statistic?

scale of measurement
dependent variable study design 

What statistical test would you use for nominal data?

singlesample Chisquare
multiplesample Chisquare 

What statistical test would you use for ordinal data?

MannWitney Utest
Wilcoxon matched pairs test KruskalWallis test 

What are the nonparametric alternatives to:
1. independent ttest 2. correlated ttest 3. oneway ANOVA 
1. MannWitney
2. Wilcoxon 3. KruskalWallis 

What statistical tests would you use for interval and ration data?

ttest
ANOVA 

Name types of ttest

simple sample
independent samples (between) correlated samples (within) 

Name types of ANOVA

oneway
factorial (2way, 3way) randomized block factorial ANCOVA repeated measures mixed (splitplot) MANOVA 

When use oneway ANOVA vs. factorial ANOVA?

oneway = 1 IV
factorial = 2+ IVs 

What are the Post Hoc tests for ANOVA?

Scheffe's S test
Tukey's HSD test Fisher's LSD test 

Which Post Hoc test is least vulnerable to Type I Error, but more vulnerable to Type II error?

Scheffe's
Tukey's 

Which Post Hoc test is least vulnerable to Type II Error, but more vulnerable to Type I error?

Fisher's


The numerator of the fratio is a measure of variablity due to...?

treatment effects & error


In ANOVA, the "mean square within" provides info about:

sampling fluctuations


Why use oneway ANOVA instead of seperate ttests?

to reduce Type I error rate


How do you calculate fratio?

MSB/MSW


How do you calculate MSB?

SSB/df


How do you calculate MSW?

SSW/df


Use: MANOVA

1+ IV
2+ DV (interval/ratio) *helps increase statistical power by assessing effects of IV on all DVs 

Ex: planned "a priori" analysis (4)

DunnBonferroni t
linear contrasts orthogonal comparisons trend analysis 

Axis on scattergram

X = IV = predictor
Y = DV = criterion 

Which correlation coefficient is most commonly used with...
1. interval and ratio data 2. rank data 3. nominal data 
1. Pearson r (also Eta)
2. Spearman rank 3. Contingency (C) 

How do you translate correlation coefficient score into something meaninful?

calculate coefficient of determination to provide a measure of shared (explained) variability.
 square the coefficient e.g. if coefficient is .60, .60 x .60 = .36, .36 x 100 = 36%, therefore, 36% of scores on DV explained by IV... remaining 64% is unexplained variance. 

Use: regression analysis

to predict a score on a criterion (DV) based on person's obtained score on predictor (IV).


How do you locate a regression line

least squares criterion


Use: multiple regression

2+ continuous or discrete predictors
1 criterion 

Ex: multiple regression

1. simultaneous (simple)
2. stepwise 3. hierarchical 

When use multiple regression instead of ANOVA?

if groups are unequal in size
if IVs on a continuous scale 

Use: canonical correlation

[an extension of mult reg]
2+ continuous predictors 2+ continuous criterions 

Ex: multivariate techniques (4)

multiple regression
canonical correlation discriminant function analysis logistic regression 

Ex: bivariate correlational techniques (2)

scattergram
correlation coefficient 

Ex: bivariate prediction (1)

regression analysis


Ex: multivariate techniques (2)

path analysis
LISREL 

Ex: correlation & prediction tehcniques (4 main)

bivariate correlational techniques
bivariate prediction multivariate techniques: correlation & prediction multivariate techniques: causal modeling 

Use: discriminant function analysis

2+ continuous predictors
1 discrete criterion 