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An opinion poll surveyed a random sample of 242 people, and the results were organized in the above table.

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ANSWER ALL QUESTIONS

A. An opinion poll surveyed a random sample of 242 people, and the results were organized in the above table. Respondents were classified by gender (female or male) and by highest education level obtained.

B. Identify whether gender has a significant impact on the highest education level by carrying out an appropriate statistical test. Briefly state your null and alternate hypothesis. Provide the appropriate code for the statistical test. 

2. To understand whether age affects the predictive risk by dose levels, and associated complication risk for one of the treatments (X), a gene expression profiling was conducted after sampling whole blood from few subjects. You may or may not consider the dose indices to have a cumulative effect i.e. you may consider these are a separate administration of the drug. 

The table shows gene expression values by defined six age categories and four dose indices administered to these subjects.   

A. Identify if gene expression is affected significantly by any of the defined age categories or dose indices in the patients treated with “X”. 

B. Explain your testing hypothesis, assumptions and interpret the results

3. Write the R-code to extract various nutritional values from different food varieties in the given nutrition  Download nutrition XML document. If someone ate all the food items at once, plot a chart to compare it to the daily value for total-fat, saturated-fat, cholesterol, sodium, carb, fiber, protein.

Find the correlation matrix between the total-fat, saturated-fat, cholesterol, sodium, carb, fiber, protein values that you extracted in Question 1. Please submit the R code and the value of Pearson's product-moment correlation

4. For the blood glucose values for subject 563 - 563-ws-training.xml Download 563-ws-training.xml - train a linear regression model on 80% of the initial data (sequential), and then test the model on the remaining 20% of the data. Train an ARIMA model (with automatic p,d,q values) on the same training set and validate on the same test set. Compare the two models by selecting appropriate metrics and explain which model should be selected.

 

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