Chi square data?

Is there a relationship between any two variables IN THE DATA?

How strong is the relationship IN THE DATA?

What is the direction and shape of the relationship IN THE DATA?

Is the relationship due to some intervening variable(s) IN THE DATA??

It is hard to answer your question without looking at data, but am gonna give you an example and hopefully you have some note of chi square test and understand the concepts of degrees of freedom, Fo=observed frequency, Fe=expected frequency, I hope your teacher gave you as well a table with the different chi square distribution values because you need to compare your values from the values in the chi square distribution table.

example

Chi-Square Test

-If of 48 students, 20 watch reality shows and 28 do not, is

there a clear preference for not watching them? It’s a

majority, but is it statistically clear?

Fo = 20 and 28

Fe = 24 and 24 (no difference)

Chi-square =

X^2 = sum((Fo-Fe)^2/Fe)=16/24 + 16/24 = 32/24 = 1.5

-alpha value of 0.05 and degree of freedom (#of independent variables-1) = 1 means a critical value for chisquare of 3.841

-Since our calculated value of 1.5 does not exceed the critical

value, we cannot reject the null hypothesis

note = alpha value of 0.05 is a general convention that if there is a probability of less than 0.05, the hypothesis will be rejected.

so once you have your chi square value you compare it to the distribution table under the degrees of freedom calculated for your experiment and always under an alpha value of 0.05