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Nickname
statkat.com ID; append to https://statkat.com/stattest.php?&t= to see
statkat.com link
FamilySubtype
Priority
Priority commentsPurposeAKADataAssumptions
Hypotheses
Sampling distribution of the test statistic
Formulas (estimators, effect size, power, CIs)
Non-parametric optionNotes
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X2Chi square test
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proportions
X2GF33Chi square test for goodness of fitP2
Check if an experimental distribution matches the theoretical expected
- The sampling method is simple random sampling
- The expected frequency count for each cell of the table is at least 5
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proportions
X2I44Chi square test of independenceP2Check for association between two categorical variables
Chi-squared test for the relationship between two categorical variables
one sample with at least two cateorical variables
- The sampling method is simple random sampling
- The expected frequency count for each cell of the table is at least 5
H0: there is no association between the two variables (independent).
HA: there is an association between the two variables.
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proportions
X2HChi square test for homogeneityP2
Check whether 2 or more independent random samples are drawn from the same population or from different populations
two samples of one categorical variable from different populations
- For each population, the sampling method is simple random sampling
- The expected frequency count for each cell of the table is at least 5
H0: proportions are the same (p1= p2= p3= …).
HA: at least one proportion is different the stated proportions .
chi square test of homogeneity is an extension of chi square test of independence.
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ZZ-Test
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numeric
Z155One sample z-test for the mean?better cover just t (otherwise too much)
Compare a sample mean to a theoretical mean, assuming population variance is known
Compare a sample independent observations with theory
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numeric
Z288Two sample z-test for the mean?better cover just t (otherwise too much)
Compare difference of sample means, assuming population variance is known
Compares two independent samples
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numeric
Z1p11z-test for a single proportionP2
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numeric
Z2p22
z-test for the difference between two proportions
P1
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TT-TestStudent's t-test
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numeric
T166One sample t-testP2
Compare a sample independent observations with theory
- n greater than 20
1-sample sign; 1-sample Wilcoxon
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numeric
T1P77Paired t-testP2
Examines a set of differences
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numeric
T21010Two sample t-testP1
Compares two independent samples
- each group should have n greater than 15
Mann-Whitney test
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numeric
T2W99Welch's t-testP2
Welch's unequal variances t-test
Compares two independent samples from populations with differet variance
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ANOVAANOVA
Analysis of Variance, F-test
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ANOVA1W1111One way ANOVAP2
Compares the menas of three or more groups
- each group should be greater than 15
Kruskal-Wallis; Mood's median test
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ANOVA1WPOne-way repeated measures ANOVAP3
One-way ANOVA paired test
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ANOVA2W1212Two-way ANOVAP3
Factorial ANOVE with two factors
Compares groups classified by two different factors
Friedman test
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TukeyTukey HSD? super important if you're covering post-hoc!
Perform pairwise comparison between all groups
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NP
Nonparametric
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SIGNSign test for a population medianP3
weaker version of Wilcoxon signed rank test that looks only at sign and not rank
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SIGNP3434Sign test for matched-pairsP4
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WSIGNEDR4242One sample Wilcoxon signed-rank testP2
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WSIGNEDRP3535Wilcoxon signed-rank test for matched-pairsP4
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WRANKSUM1414Mann-Whitney U-testP3?
Wilcoxon rank sum test, Unpaired two-samples Wilcoxon test
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KW1717
Kruskal-Wallis analysis of variance by ranks
P3
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FRI3333Friendman test?
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FE
Fisher's exact test
in RP3on biostathandbook
see also Barnard's test
2x2 contingency table
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RRegression
Analysis of Variance, F-test
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T2RRegression coefficient test?P3this is pretty similar in process to a one-sample t-test!test for correlation coeff
Measure the linear association between two variables
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REG1313Regression (OLS)P1test for y-intercept or slope (any regression coefficient)
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LOGREG2020Logistic regressionP3logit(LinearRegression)
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MREG2525Multivariate regressionP3LogisticRegression with multiple input variables
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MLOGREG2121Multinomial logistic regressionP4
special case of the above, via pre-computations (design matrix)
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OLOGREG2222Ordinal logistic regression?this might be more important for business people, because I see WAY TOO MANY people treating their ordinal variables as continuous...its one of the most common handful of consults I get
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Spearman Rank Correlation
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CORRCorrelation
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PEAR1919Pearson correlationP2
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SPEAR1818Spearman rhoP3
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Distribution checks
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Kolmogorov-Smirnov TestP3
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Shapiro-Wilk test for normalityP4
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D’Agostino and Pearson’s test based on skew and kurtosis
P99
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Anderson-Darling test for data coming from a particular distribution
P99
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MANOVA1W1515Multivariate analysis of variance
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MANOVA2W1616
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4444Binomial test for a single proportion
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ANCOVA2323ANCOVA
Linear regression with a mix of caregorical and continuous variables
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MANCOVA2424MANCOVA
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ANOVAP
2828Repeated measures ANOVARMA
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2929Repeated measures ANCOVA
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?P3939McNemar's test
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?P4040Cochran's Q test
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Mood's median test
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