Statistical tests inventory

	A	B	C	D	E	F	G	H	I	J	K	L	M	N	O	P	Q
1		Nickname	statkat.com ID; append to https://statkat.com/stattest.php?&t= to see	statkat.com link	Family	Subtype	Priority	Priority comments	Purpose	AKA	Data	Assumptions	Hypotheses	Sampling distribution of the test statistic	Formulas (estimators, effect size, power, CIs)	Non-parametric option	Notes
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3		X2			Chi square test
4	proportions	X2GF	3	3		Chi square test for goodness of fit	P2		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
5	proportions	X2I	4	4		Chi square test of independence	P2		Check 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.
6	proportions	X2H				Chi square test for homogeneity	P2		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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10		Z			Z-Test
11	numeric	Z1	5	5		One 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
12	numeric	Z2	8	8		Two 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
13	numeric	Z1p	1	1		z-test for a single proportion	P2
14	numeric	Z2p	2	2		z-test for the difference between two proportions	P1
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19		T			T-Test					Student's t-test
20	numeric	T1	6	6		One sample t-test	P2				Compare a sample independent observations with theory	- n greater than 20				1-sample sign; 1-sample Wilcoxon
21	numeric	T1P	7	7		Paired t-test	P2				Examines a set of differences
22	numeric	T2	10	10		Two sample t-test	P1				Compares two independent samples	- each group should have n greater than 15				Mann-Whitney test
23	numeric	T2W	9	9		Welch's t-test	P2			Welch's unequal variances t-test	Compares two independent samples from populations with differet variance
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27		ANOVA			ANOVA					Analysis of Variance, F-test
28		ANOVA1W	11	11		One way ANOVA	P2				Compares the menas of three or more groups	- each group should be greater than 15				Kruskal-Wallis; Mood's median test
29		ANOVA1WP				One-way repeated measures ANOVA	P3			One-way ANOVA paired test
30		ANOVA2W	12	12		Two-way ANOVA	P3			Factorial ANOVE with two factors	Compares groups classified by two different factors					Friedman test
31					Tukey			Tukey HSD? super important if you're covering post-hoc!			Perform pairwise comparison between all groups
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34		NP			Nonparametric
35		SIGN				Sign test for a population median	P3				weaker version of Wilcoxon signed rank test that looks only at sign and not rank
36		SIGNP	34	34		Sign test for matched-pairs	P4
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38		WSIGNEDR	42	42		One sample Wilcoxon signed-rank test	P2
39		WSIGNEDRP	35	35		Wilcoxon signed-rank test for matched-pairs	P4
40		WRANKSUM	14	14		Mann-Whitney U-test	P3?			Wilcoxon rank sum test, Unpaired two-samples Wilcoxon test
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43		KW	17	17	Kruskal-Wallis analysis of variance by ranks		P3
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46		FRI	33	33	Friendman test		?
47		FE			Fisher's exact test	in R	P3		on biostathandbook	see also Barnard's test	2x2 contingency table
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50		R			Regression					Analysis of Variance, F-test
51		T2R				Regression coefficient test?	P3	this is pretty similar in process to a one-sample t-test!	test for correlation coeff		Measure the linear association between two variables
52		REG	13	13		Regression (OLS)	P1		test for y-intercept or slope (any regression coefficient)
53		LOGREG	20	20		Logistic regression	P3		logit(LinearRegression)
54		MREG	25	25		Multivariate regression	P3		LogisticRegression with multiple input variables
55		MLOGREG	21	21		Multinomial logistic regression	P4		special case of the above, via pre-computations (design matrix)
56		OLOGREG	22	22		Ordinal 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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59																Spearman Rank Correlation
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61		CORR			Correlation
62		PEAR	19	19		Pearson correlation	P2
63		SPEAR	18	18		Spearman rho	P3
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66					Distribution checks
67						Kolmogorov-Smirnov Test	P3
68						Shapiro-Wilk test for normality	P4
69						D’Agostino and Pearson’s test based on skew and kurtosis	P99
70						Anderson-Darling test for data coming from a particular distribution	P99
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82		MANOVA1W	15	15		Multivariate analysis of variance
83		MANOVA2W	16	16
84			44	44		Binomial test for a single proportion
85		ANCOVA	23	23		ANCOVA			Linear regression with a mix of caregorical and continuous variables
86		MANCOVA	24	24		MANCOVA
87		ANOVAP	28	28		Repeated measures ANOVA				RMA
88			29	29		Repeated measures ANCOVA
89		?P	39	39		McNemar's test
90		?P	40	40		Cochran's Q test
91						Mood's median test
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