SG 10

Question 1

require a number of assumptions about one or more population parameters

Answer 1

Parametric methods

Question 2

distribution-free methods

Answer 2

nonparametric

Question 3

ADVANTAGES OF NONPARAMETRIC METHODS

Answer 3

• When the underlying probability distribution is unknown or is known to be different from what a parametric method requires.
• When the level of measurement falls below what is required by a parametric technique.
• When there is no suitable parametric technique.

Question 4

In Chi-square, the distribution tends to shift to the ____ and become more spread out with____df values.

Answer 4

right
larger

Question 5

Chi-square

Answer 5

test for independence

Question 6

The degree of skewness also decreases with increasing df such that the chi-square distribution approaches a normal distribution. t or f

Answer 6

t

Question 7

Chi-square cannot be negative since it sums squared differences divided by ______

Answer 7

positive expected frequencies

Question 8

properties of chi-square

Answer 8

• It cannot be negative since it sums squared differences divided by positive expected frequencies
• It is skewed to the right.

Question 9

Two variables are______ if, for all cases, the classification of a case to a particular category of one variable has no effect on the probability that the case will fall into any particular category of the second variable.

Answer 9

independent

Question 10

• it means having a particular attribute will have no effect on having another attribute

Answer 10

Independence

Question 11

test for independence (chi-square) 3 assumptions

Answer 11

Independent random samples
Nominal variables
Data must be organized in a contingency table

Question 12

displays the scores on two or more variables at the same time

Answer 12

Contingency table

Question 13

3 Limitations of the Chi-square Test

Answer 13

• Data must be in the form of frequencies (i.e. counted data within categories).

The contingency tables = at least two columns.

Expected frequencies of any cell should not be less than 5 (although it is permissible for 20% of cells if the contingency table is larger than 2x2)

Question 14

the absolute value of the difference between the observed and expected frequencies for each cell

Answer 14

Yates’ Continuity Correction

Question 15

• corrected chi-square
• the absolute value of the difference between the observed and expected frequencies for each cell

Note: For larger tables, there is no correction formula for computing chi-square

Answer 15

Yates’ Continuity Correction

Question 16

Used to determine if the observed frequencies differ significantly from an even distribution. In other words, it determines whether the sample data is consistent with a hypothesized distribution

Answer 16

Chi-square test

Question 17

______ is applicable for one categorical variables from a single population.

Answer 17

Chi-square test

Question 18

Chi-Square Test: Goodness-of-Fit-Test

Answer 18

if the observed and expected frequencies are similar, it is said that there is a “good fit”

Question 19

Chi-square test 2 assumptions

Answer 19

Independent random samples
The expected frequency of each category must be at least 5

Question 20

• It is useful when there are cell frequencies less than 5.
• It is therefore useful in the same situation as the chi-square test.
• It avoids the main limitation of the chi-square, which is sufficient observations within each cell. It circumvents this limitation by comparing cumulative frequencies rather than cell frequencies.

Answer 20

K-S T-S T

Question 21

• This test determines if there is statistical difference between two independent samples.
• more than 2 groups

Answer 21

Kolmogorov-Smirnov Two-Sample Test

Question 22

Kolmogorov-Smirnov Two-Sample Test 3 Assumptions

Answer 22

Assumptions:
Unless sample sizes are equal, this can only be used if both samples sizes > 40
Independent random samples
At least ordinal-scale categories

Question 23

• It can be applied to small samples and is useful for samples with unequal sizes.

Answer 23

mann-whitney U test

Question 24

• It is also called the Wilcoxon Rank-Sum Test.
• It is a test of equality between two independent samples.
• It can be applied to small samples and is useful for samples with unequal sizes.
• <20 samples

Answer 24

Mann-Whitney U Test

Question 25

test of independence =
test of equality (small/unequal sample) =
test of statistical difference of 2 samples (less than 5 frequency) =
test of equality 2 or more using variance =
test for medians =
statistical difference when HO is rejected =
abs value of the diff between O and E frequency =

Answer 25

chi-square test
mann-whitney U test
k-s t-s t
anova
kw h test
flsdt
yates’ cc