Question

Q1)When should I use the Shapiro-Wilk test?

Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal.

A.

Compare two treatment groups when a normal distribution cannot be assumed.

B.

More than two treatment groups where a normal distribution can be assumed.

C.

Test to see if the frequency data from a population fit a discrete probability distribution.

D.

Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis.

E.

Test the fit of the normal distribution to the data set.

F.

Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance.

G.

Test to compare frequency data to a specific population model

H.

Compare more than two treatment groups when a normal distribution cannot be met.

I.

Test if the median of a data set equals a null hypothesized value when the distribution of the data does not meet the assumption of normalacy.

J.

Compare two treatments consisting of paired data where a normal distribution can be assumed.

K.

Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean.

L.

Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution.

M.Compare two treatment groups consisting of paired data when the data do not fit the normal distribution.

Q2)

When should I use the Sign Test (single variable)?

Remember that some tests, such as chi squared, can be used under various circumstances. The goal of the test changes based on the situation. Pay attention to the specific conditions noted in parenthesis to ensure you are picking the correct goal.

	A.	More than two treatment groups where a normal distribution can be assumed.
	B.	Test to compare frequency data to a specific population model
	C.	Compare two treatment groups consisting of paired data when the data do not fit the normal distribution.
	D.	Compares numerical data to a known mean. The null hypothesis is that the mean of the data equals the known mean.
	E.	Compare categorical frequency data with an expected population proportion. No difference between observed and expected proportions is used as the null hypothesis.
	F.	Compare two treatment groups when a normal distribution cannot be assumed.
	G.	Test the fit of the normal distribution to the data set.
	H.	Test to see if the frequency data from a population fit a discrete probability distribution.
	I.	Compare two treatments consisting of paired data where a normal distribution can be assumed.
	J.	Compare two treatment groups consisting of independent samples with a normal distribution AND unequal variance.
	K.	Compare two treatment groups of independent samples where the data meet the assumption that the data fit the normal distribution.
	L.	Compare more than two treatment groups when a normal distribution cannot be met.
	M.	Test if the median of a data set equals a null hypothesized value when the distribution of the data does not meet the assumption of normalacy.

Answer 1

Q1) Shapiro wilks test is used to test the normality of the data. Similar test is Kolmogrov-Srirnov test

A. Mann- Whitney test

B. ANOVA

C. Chi-Square test

D. Chi-Square test

E. Kolmogrov- Smirnov test

F. Independent Sample T test with unequal variance

G. Chi-Square test

H. Kruskal-Wallis test

I. Independen Sample Median test

J. Paired t - test

K. One Sample t-test

L. Independent Sample T test with/without unequal variance

M. Wilcoxon Rank Sum Test

Q2) When you need to compare numerical data mean to a hypothesied mean

A. ANOVA

B. Chi-Square test

C. Wilcoxon Rank Sum Test

D. One Sample t-test

E. Chi-Square test

F. Mann- Whitney test

G. Kolmogrov-Smirnov and Shapiro-Wilks

H. Chi-Square

I. Paired t-test

J. Independent Sample T test with unequal variance

K. Mann- Whitney test

L. Kruskal-Wallis test

M. Wilcoxon Rank Sum Test