Chi square

Question 1

parametrics stats assumptions

Answer 1

Sample is large enough
comes from normal distribution
homogeneity

Question 2

What do we do when assumptions are not met?

Answer 2

Use non-parametric Statistics

Question 3

Non-parametric Statistics

Answer 3

• distribution free

- allows to analyze different data

Question 4

Chi-Square X2

Answer 4

allows to determine if what you observe in a distribution is what would be expected by chance alone

Question 5

number of dimensions

Answer 5

one sample:majors
two sample: majors by class year
Given no other information you expect categories to be equal

Question 6

examples of when to use chi square

Answer 6

Gambling–> is it fair

criminal justice–> are police in wichita engaging in social profiling?

Question 7

chi-square equation

Answer 7

X2 = ∑ (O-E)2/ E

X2 = Test statistic
O = Observed Frequency
E = Expected Frequency (By chance)

Question 8

computing chi square

Answer 8

Null and Research Hypothesis (Words and Symbols)
Compute the Test Statistic
Determine if it is significant or not
Write a 2-3 sentence results section, including a numerical X2 statement.

Question 9

hypotheses

Answer 9

Null hypothesis
H0: P1 = P2 = P3
Research hypothesis
H1: P1  P2  P3

Question 10

Chi Square Example

Answer 10

Is the distribution of answers different than we would expect by chance?
Null Hypothesis: The responses not different than expected by chance
Research Hypothesis: The responses are different than expected by chance, reflecting some underlying preference

Question 11

questions to ask ourselves

Answer 11

What’s our research question?
What’s our null hypothesis?
What’s our research hypothesis?

Question 12

Table steps

Answer 12

Category/ O/E/D/(O-E)2/(O-E)2/E

Question 13

Presenting Your Results (example)

Answer 13

x2(2) = 20.6, p < .05
x2  represents the test statistic
2 is the number of degrees of freedom
20.6 is the obtained value
p < .05 is the probability