1. Find a bar plot in the media or online. Include an image of the graph you found, not just the link. Hint: Google "bar plot," "bar graph," or "bar chart." Choose a graph with a topic that is interesting to you since you will be using this graph for Parts 1 and II of this project. The vertical scale can be given in frequencies (count) or relative frequencies (proportions).Be sure that the graph is depicting real data, not made-up data.
3. Identify the categorical variable being depicted.
5. Answer questions:What is the most common category and least common category?
6. What is the relative frequency for the most common category? Note: this is the value forthat you will use in part F. below.
7. Conjecture the number of individuals in the most common category if there were 5,000 individuals included.
9. Is there anything misleading about the graph? Give at least one way to improve the graph. Was a valid sampling method used to obtain the data? If so, explain and identify the name of the sampling method given. If not (or if this information is not given), describe a valid sampling method (in detail and in context) that could have been used and identify the name of the sampling method you described.
11. Carry out a simulation for the most common category. Assume a sample of size 100 and. Complete 50 trials of the simulation using the RossmanChance applet athttp://www.rossmanchance.com/applets/OneProp/OneProp.htm. Take a snip or screenshot of the resulting dot plot. Compute a two-sided p-value for the most common category in your graph. Based on your p-value, what is the appropriate conclusion for a test of these hypotheses:

. Using your graph fromPart I, suppose you are interested in p for the most common category. State whatrepresents in context. Check the conditions for computing a 95% confidence interval for. State whether or not the conditions are met and whether you believe the results you obtain in part C. will be valid. Compute and interpret the confidence interval. Show your work (include the technology inputs you used). Check the conditions for carrying out a two-sided test of whether. State whether or not the conditions are met and whether you believe the results you obtain in part E. will be valid. Note: two of the conditions are the same as the ones you checked in part B., but one condition will require a different calculation. Show all the steps for the hypothesis test and state your conclusion in context. Show your work (include the technology inputs you used). Compare your results to the ones you obtained using simulation inPart I. Include the image of your results fromPart Iagain in this part. How similar were they? Using your results when you checked the conditions in step D. above, explain the similarities or differences between your results inPart IandPart II. Is one more valid than the other? Why? . Ho: P = 0.5 HA: P =/ 0.5 . Carry out a simulation for the most common category. Assume a sample of size 100 andp= 0.5. Complete 50 trials of the simulation using the RossmanChance applet athttp://www.rossmanchance.com/applets/OneProp/OneProp.htm. Take a snip or screenshot of the resulting dot plot. Compute a two-sided p-value for the most common category in your graph. Based on your p-value, what is the appropriate conclusion for a test of these hypotheses: Ho: P = 0.5 HA: P = / 0.5