PARAMETRICS DEFINITIONS

Question 1

Kruskal-Wallis test

Answer 1

test identifies whether one of the groups is systematically different from the others

Question 2

Kruskal-Wallis test example

Answer 2

x

Question 3

Kruskal-Wallis test example

Answer 3

If p-value is smaller than , sufficient evidence exists to reject the null hypothesis. Conclude that at least one of the samples comes from a different distribution.

If p-value is greater than , insufficient evidence exists to reject the null hypothesis. Conclude that all of the samples come from the same distribution.

Question 4

Wilcoxon

Answer 4

This method ignores the values of the original data and compares the sum of the two groups’ ranks

Question 5

Wilcoxon assumption

Answer 5

This test assumes that the two groups come from similar distributions. Another assumption of the Wilcoxon rank-sum test is that the two sets of data are independent.

Question 6

Wilcoxon Sample

Answer 6

x

Question 7

Wilcoxon Two Sided

Answer 7

Test is often two-sided.
where is the minimum sum of the ranks.
If the p-value is less than , sufficient evidence exists to reject the null hypothesis. In other words, statistical evidence suggests that the groups have different medians.
If the p-value is greater than , insufficient evidence exists to reject the null hypothesis. In other words, statistical evidence suggests that the groups have same median.

Question 8

Wilcoxon One Sided

Answer 8

A one-sided test is also possible.
where and are the sum of the ranks for each sample.
If the p-value is less than , sufficient evidence exists to reject the null hypothesis. In other words, statistical evidence suggests that the groups have different medians.
If the p-value is greater than , insufficient evidence exists to reject the null hypothesis. In other words, statistical evidence suggests that the groups have same median.

Question 9

student’s t-distribution or t-distribution

Answer 9

used in place of the normal distribution in situations where the sample size () is small or the population standard deviation () is unknown

Question 10

t-statistic

Answer 10

btained from a sample assumed to have a t-distribution and involves the population mean and a larger variability from estimating the population standard deviation

Question 11

null hypothesis

Answer 11

hypothesis of no difference

Question 12

alternative hypothesis

Answer 12

claim contrary to the null hypothesis.

Question 13

two-sample t-test

Answer 13

used to determine if a statistically significant difference exists between two population means

Question 14

paired t-test or dependent t-test,

Answer 14

sample taken from one population is exposed to two different treatments.

Question 15

paired t-test or dependent t-test, Example

Answer 15

A group of professional cycling athletes is selected for a study on the effects of caffeine dosage on exhaustion times. The populations are the cyclists for each of two dosages. The samples are the measured exhaustion times for each dosage, which implies dependence because the measurements were taken from the same group.

Question 16

unpaired t-test or independent t-test,

Answer 16

ample taken from one population is not related to a different sample taken from another population

Question 17

unpaired t-test or independent t-test, Example

Answer 17

Ex: The effect of caffeine intake on exhaustion times is studied by measuring the exhaustion times of a randomly selected group of 9 professional cyclists taking caffeine pills and another group of 9 cyclists not taking caffeine pills. The two populations are all cyclists taking caffeine pills and those who are not taking the pills. The samples are the measured exhaustion times from the two groups, each with 9 cyclists, which implies independence because the times are for two different groups of cyclists.