Question

A classic data set for investigating categorical variables deals with the RMS Titanic. The Titanic sank in the North Atlantic Ocean on April 15, 1912. There were more than 2,000 passengers and crew on board and more than 1,500 did not survive. The data set titanic.jmp located with this homework contains data on 887 passengers. For each passenger, the variables Class (class of the passenger) and Survived (whether or not the passenger lived) were recorded. A main question of interest is whether there is an association between class and survival.

1. Identify the Who for this data set.
2. Identify the What for this data set.
3. Use JMP to obtain the distribution of the variable Survived. Print out the output and turn it in with this assignment. See the Chapter 2 JMP guide for help.
4. What proportion of these passengers did not survive?
5. One variable that could be associated with the survival of a passenger is their Class. In studying this relationship, which variable is the explanatory variable? Circle the appropriate answer. Class Survived
6. Use JMP to obtain a contingency table and mosaic plot of the relationship between the Class of a passenger and whether or not they Survived. Change the contingency table so that it includes only the Count and Row % values. Print out the output and turn it in with this assignment. See the Chapter 2 JMP guide for help.
7. Explain the meaning of the number 119 from the contingency table.
8. Give the conditional distribution of Survived given that the passenger was in First class.
9. Compare this conditional distribution to the overall marginal distribution of Survived. Are the two distributions similar to each other, or are they different? Explain.
10. Based on the contingency table and mosaic plot, does it appear there is an association between Class and Survival? Circle the appropriate answer below. Then given an explanation for your answer. Yes, there is an association No, there is not an association Explain your answer:

Answer 1

The data set's 'Who' is the 887 Titanic passengers, and the 'What' includes their class and survival status. 'Class' is the explanatory variable when studying the association with survival. An analysis using a contingency table and mosaic plot in JMP would reveal if an association between class and survival exists.

Step-by-step explanation:

The Who in this data set refers to the 887 passengers on board the RMS Titanic whose data is recorded in the titanic.jmp file.

The What comprises two categorical variables for each passenger, which are Class (the class in which the passenger traveled) and Survived (whether or not the passenger lived).

To analyze the distribution of the variable Survived, one would use the statistical software JMP to generate a distribution chart.

This will show the count and proportion of passengers who survived and who did not. Unfortunately, as a tutor providing text-based assistance, I'm unable to use JMP or provide printed outputs.

However, you can review the Chapter 2 JMP guide to accomplish this task and calculate the proportion of passengers who did not survive.

The variable Class is considered the explanatory variable when studying its relationship to survival.

A contingency table and mosaic plot can be produced using JMP to examine the association between passenger class and survival rates.

The output should be adjusted to show Count and Row percentages.

If the contingency table shows '119' in a specific cell, it is the count of passengers who belonged to a particular class and either survived or did not survive.

The meaning of this number depends on its context within the contingency table.

The conditional distribution of Survived given the passenger was in First class can be assessed by looking at the row percentages in the contingency table.

This distribution should be compared with the overall marginal distribution to determine if they differ significantly.

To determine if there is an association between passenger class and survival, one would analyze the contingency table and the mosaic plot.

If the survival rates differ noticeably across classes, this suggests an association exists.

Based on the pattern of the table and plot, you can then conclude whether or not an association is present.

Answer 2

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