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Match the health disparity to the correct racial/ethnic group. Use the process of elimination to match the disparity to the group that is most highly affected. Use each racial/ethnic group only once. There may be some choices that are never used. (2 pts each)

Now please show the area around your desk/table. This is not a 360o room scan. I only need a view of the area around your computer, similar to the image below. If you need to use your computer to do the scan (webcam embedded), then I wouldn’t expect to see your computer during the scan.

The first set of questions require you to match health disparities/inequities to the racial/ethnic group MOST affected.  Although some diseases or problems may be a disparity/inequity for more than one group, there is only one correct racial/ethnic group for each disease or problem. Use the process of elimination to rule out implausible answers and select the best choice. There may be some choices that are never used.

Question 2: Statistical Significance – 6 points For this question, use the unstandardized trainData. In model1, which regression coefficients are significant at the 95% confidence level? Are these the exact same regression coefficients that are significant at the 90% confidence level? (2 points) Build a new model using only the variables whose coefficients were found to be statistically significant at the 95% confidence level. Call it model2. Display the model summary. Using model2, interpret the coefficient of bp in the context of the data description. State any assumptions while interpreting the coefficient. (2 points) Perform a Partial F-test to compare the reduced model (model2) with the full model (model1) and interpret it at the 95% confidence level. Which one would you prefer? Is it good practice to select variables based on the statistical significance of individual coefficients? Why or why not? (2 points)

Listen to the question and write a logical answer  in a complete sentence IN SPANISH Copy and Paste these characters when necessary á   é    í   ó   ú   ñ

Question 6: Prediction – 9 points For this question, use the testData. a. Using previously built models listed below, predict the Target variable and output the average response for each of the models. Summarize the results: i) Full linear regression model from question 1a (model1) ii) Reduced model from question 2b (model2) iii) Stepwise forward-backward model from question 3b (both_model) iv) Elastic Net model from question 5d (enet.model) b. Using the first row of testData, calculate the 99% prediction interval using model2 (reduced model).    c. (Note: No code is required to answer Q6c) Discuss the trade-offs and considerations involved in selecting the best predictive model for diabetes disease progression from the following approaches: forward stepwise regression, best subset selection using Mallow’s Cp, ridge regression, and elastic net regression. In your discussion, address the following points: (4 points) Model Complexity vs. Interpretability: How does each method balance model complexity and interpretability? Which methods tend to produce more interpretable models, and which ones might lead to more complex models? Handling Multicollinearity: Explain how each method deals with multicollinearity among predictors. Which methods are more effective in reducing the impact of multicollinearity, and why? Bias-Variance Trade-Off: Compare the expected bias-variance trade-off for each method. Which methods are likely to provide the best balance between bias and variance, and what are the potential drawbacks of these methods? Practical Considerations: Discuss any practical considerations, such as computational efficiency, ease of implementation, and the availability of software tools, that might influence the choice of method in a real-world scenario.

.Listen to the question and write a logical answer  in a complete sentence IN SPANISH Copy and Paste these characters when necessaryá  é  í  ó  ú  ñ 

LISTENING:: Listen to the recording.  Answer the questions in COMPLETE SENTENCES IN SPANISH.  Copy and paste the questions and write your answers in the answer space.    á  é  í   ó   ú   ñ   1. ¿Nora está en el restaurante para desayunar, almorzar o cenar? 2. ¿Qué recomienda el camarero? 3. ¿Qué le gustaría probar a Nora? 4. ¿Por qué no quiere pedir café? 5. ¿Qué pide para beber?