THIS IS THE QUESTION----6.1 #6, Should the difference for Go without essentials be rejected at the .001 level? Explain your reasoning.

STATISTICAL GUIDE The chi-square test looks to see if there are differences between groups, just as many other statistical tests do (e.g., t-test or ANOVA). What is unique about the chi-square test is that it is designed to study group differences that are frequencies. Percentages are a common form of frequency, and so the chi-square test is often used to look at differences in percentages between two groups. For example, say you are interested to see if different percentages men and women endorse a certain political belief. Say 52% of men in a sample endorse the belief, while 73% of women endorse it. You would use the chi-square test to see if this difference was statistically significant. Just like the t-test and ANOVA, chi-square test results have a p value associated with them. The p values are interpreted in the same way as with other testsif p<.05 then the result is considered to be statistically significant. symbol for chi-square test x2 background note although it traditional report values of with associated probabilities some researchers only as in excerpt below. because decisions are based on probability levels results can interpreted without p. from research article thirty-five people were recruited through abd brain dysfunction case management and accommodation services those alcohol-related injury addition healthy community volunteers advertisements. this control group was matched clinical sample a number relevant demographic variables including age gender main source income also closely possible years education national adult reading test.... table percentage participants money problems groups p problem atm don often check change pay bills or rent late thrown out owe debts spend all within first few days go essentials very problematic impulse buying things they like need borrow .001 .064 .219 .371 .166 .010 .009 .000 .003 .036 note. teller machine. statistical guide looks see if there differences between just many other tests do t-test anova what unique about that designed study frequencies. percentages common form frequency so used look at two groups. example say you interested different men women endorse certain political belief. belief while it. would use difference have value them. same way testsif machine>