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A Research Team Wanted to Assess the Relationship Between Age

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A research team wanted to assess the relationship between age, systolic blood pressure, smoking, and risk of stroke. A sample of 150 patients who had a stroke is selected and the data collected are given below. Here, for the variable Smoker, 1 represents smokers and 0 represents nonsmokers.
A research team wanted to assess the relationship between age, systolic blood pressure, smoking, and risk of stroke. A sample of 150 patients who had a stroke is selected and the data collected are given below. Here, for the variable Smoker, 1 represents smokers and 0 represents nonsmokers. Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the Risk of stroke using a regression tree. Use Risk as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 74, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree, Best pruned tree, and Minimum error tree. Generate a Detailed Scoring report for all three sets of data. a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree. b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data? c. What is the average error on the validation data and test data? What does this suggest? d. By examining the best pruned tree, what are the critical variables in predicting the risk?
A research team wanted to assess the relationship between age, systolic blood pressure, smoking, and risk of stroke. A sample of 150 patients who had a stroke is selected and the data collected are given below. Here, for the variable Smoker, 1 represents smokers and 0 represents nonsmokers. Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the Risk of stroke using a regression tree. Use Risk as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 74, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree, Best pruned tree, and Minimum error tree. Generate a Detailed Scoring report for all three sets of data. a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree. b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data? c. What is the average error on the validation data and test data? What does this suggest? d. By examining the best pruned tree, what are the critical variables in predicting the risk?
A research team wanted to assess the relationship between age, systolic blood pressure, smoking, and risk of stroke. A sample of 150 patients who had a stroke is selected and the data collected are given below. Here, for the variable Smoker, 1 represents smokers and 0 represents nonsmokers. Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the Risk of stroke using a regression tree. Use Risk as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 74, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree, Best pruned tree, and Minimum error tree. Generate a Detailed Scoring report for all three sets of data. a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree. b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data? c. What is the average error on the validation data and test data? What does this suggest? d. By examining the best pruned tree, what are the critical variables in predicting the risk?
A research team wanted to assess the relationship between age, systolic blood pressure, smoking, and risk of stroke. A sample of 150 patients who had a stroke is selected and the data collected are given below. Here, for the variable Smoker, 1 represents smokers and 0 represents nonsmokers. Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the Risk of stroke using a regression tree. Use Risk as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 74, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree, Best pruned tree, and Minimum error tree. Generate a Detailed Scoring report for all three sets of data. a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree. b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data? c. What is the average error on the validation data and test data? What does this suggest? d. By examining the best pruned tree, what are the critical variables in predicting the risk?
Partition the data into training (50 percent), validation (30 percent), and test (20 percent) sets. Predict the Risk of stroke using a regression tree. Use Risk as the output variable and all the other variables as input variables. In Step 2 of XLMiner's Regression Tree procedure, be sure to Normalize input data, to set the Maximum #splits for input variables to 74, to set the Minimum #records in a terminal node to 1, and specify Using Best prune tree as the scoring option. In Step 3 of XLMiner's Regression Tree procedure, set the maximum number of levels to 7. Generate the Full tree, Best pruned tree, and Minimum error tree. Generate a Detailed Scoring report for all three sets of data.
a. In terms of number of decision nodes, compare the size of the full tree to the size of the best pruned tree.
b. What is the root mean squared error (RMSE) of the best pruned tree on the validation data and on the test data?
c. What is the average error on the validation data and test data? What does this suggest?
d. By examining the best pruned tree, what are the critical variables in predicting the risk?

Definitions:

Pluralism

A societal condition or system in which multiple distinct ethnic, religious, or cultural groups coexist within the same society, maintaining their individual traditions.

Racial Diversity

The inclusion and representation of individuals from a variety of racial and ethnic backgrounds in a group or organization.

Ethnic Diversity

Ethnic diversity refers to the presence of multiple ethnic groups within a given society, each with its distinct culture, traditions, and sometimes language.

Genocide

The deliberate and systematic extermination of a racial, ethnic, national, or cultural group.

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