1. What is statistical significance? 2. Why is it "harder" to find a significant outcome (all other things being equal) when the research hypothesis is being tested at the 0.01 rather than the 0.05 level of significance? 3. Discuss the general idea that just because two things are correlated, one does not necessarily cause the other. Provide an example other than ice cream and drowning or coffee consumption >4cups/day and skin cancer. Research Question 1: Is there a difference between smoking behaviour (non-smoker, current smoker, or past smoker) and gender (male or female)? We could use a chi-square test to determine if there is a significant association between gender and smoking behaviour. 1. State the null and research hypotheses? 2. Decide on a confidence level? 3. What is the p-value cut-off? 4. Why are we using a chi-square test? Explain. 5. Interpret the findings? 6. Do you accept or reject the null? Do you smoke cigarettes? ' Gender Crosstabulation Count Gender Male |Female Total Do you smoke Nonsmoker Smoking Gender 49 148 297 ids cigarettes? Past smoker 13 24 37 Current smoker 31 37 68 20183 Nonsmoker Male Total 193 209 402 20230 Nonsmoker Male 20243 Past smoker Female 20248 Current sm. Chi-Square Tests 20255 Nonsmoker Female Asymptotic Significance Value 01 (2-sided) 430 49821 Past smoker Female Pearson Chi-Square 3.171 205 431 49838 Nonsmoker Male Likelihood Ratio 3.217 200 432 49854 Linear-by-Linear Male 1.106 293 Association 433 49879 Nonsmoker Male N of Valid Cases 402 434 49931 Nonsmoker Male a. Q cells (D.0%) have expected count less than 5. The minimum 435 49947 Nonsmoker Female expected countis 17.76. *Note cases represent subjects, and each subject appears only once in the dataset. That is, each row que subiec