4. Produce a segmented bar graph to display the conditional proportions who gave blood in these two years. Comment on what the graph and your calculations from #3 reveal about these two samples. at the bottom of the onenote! 5. Use the Two Proportions applet to conduct a sim- Sample dalm(2x2: E) ulation analysis to approximate a p-value for testing Group A Group B Totals the hypotheses that you stated in #2. You can enter Success 210 230 440 the table of counts in the 2 x 2 table or type in the table in the Sample data box and press Use Table. Failure 1152 1 106 2258 Or you can copy the data from the text webpage and Sample dala:(2x2: =] paste into the Sample data box and press Use Data. Verify the segmented bar graph that you created. (explanatory, response) 2002 2004 donated 210 230 didn't 1152 1106 KEYIDEA Shuffling is an appropriate way to estimate a p-value for comparing groups regardless of the study design (observational study or experiment, random assignment or random sampling or neither). Of course, the study design is very important in determining the appropriate scope of conclusions. (Can you generalize to a larger population? Can you infer a cause-and-effect conclusion?) 6. Check the Show Shuffle Options box, ask for 1000 repetitions, and press Shuffle. a. Indicate how to find the p-value from the null distribution. (Hint: Remember whether the alternative hypothesis is one-sided or two-sided.) Use "Count Samples" Windows and "Cmd + E" in c. Based on this p-value, do the sample data provide much evidence that the population Mac. proportion who gave blood in 2002 differs from the population proportion who gave blood in 2004? No, there is no evidence the proportions are different. 7. Does the null distribution of the simulated Pan - Pop values appear to follow an approximately normal distribution? Centered around what value? Also report the stan- dard deviation of these values. Approximately normal? yes Mean: 0 SD: .014 B. Let's see what the standardized statistic tells us. a. Report the observed value in the sample for the statistic Pay