Blog

Despite all its virulence factors, what type of pathogen is pseudomonas aeruginosa?

Which occupation would hold highest risk of Glanders disease?

Two lesser known NLF – GNR found in water and are known to be resistant to disinfectants

Which organism is the most common cause of Bacterial Gastroenteritis worldwide and distinguished by ‘Bloody Diarrhea”?

A nonfermenting gram-negative bacillus is isolated from a wound. The nitrate and oxidase are strongly positive.  The growth on sheep blood agar has a grape-like odor and is Beta hemolytic. The organism is presumptively:

What is the causative agent of Glanders disease?

What organism may play a role in Guillain-Barre syndrome(GBS)? 

Which of the following IS NOT a key characteristic of Pseudomonas aeruginosa?

Gradescope submission link for Question 2: Fall2025 Midterm1 Question2 Question 2: Multiple linear regression  (30 points)  Use trainData dataset for parts (a)-(d) and use the  testData for part (e). a) Fit a regression model predicting salary using the following predictors: ‘education_level’, ‘has_certification’, and ‘years_experience’. Call it model1. Display the summary. Interpret the coefficient of ‘has_certification’. State any assumptions while interpreting the coefficient. (3 points) b) Refit model1 and add an interaction term education_level * has_certification. Call it model2. Display the summary.  (2 points)i) Is the interaction term significant at a level of  0.01? (1 point)ii) Interpret the coefficient of the interaction term education_levelMasters:has_certification1. State any assumptions while interpreting the coefficient. Note: Interpret the coefficient irrespective of its statistical significance. (3 points)iii) Calculate the Variance Inflation Factor (VIF) for each predictor group in your model, where each group represents all the dummy variables created for a given categorical variable (such as all the dummies for education level), or for an interaction term (such as all dummies in educationlevel × hascertification). Report the overall VIF for each predictor group, not just for individual dummy variables. Based on these VIF values, which predictors show potential multicollinearity issues? Explain why the interaction terms have higher VIFs than the main effects. (3 points) c) Based on your model in Q2a, predict the expected salary of a Bootcamp graduate with 3 years of experience and a certification. Explain your results. (3 points) d) Fit a regression model predicting salary using num_internships, years_experience, and education_level. Call it model3. Display the summary. (2 points)i) Based on your model (model3), how much higher would you expect the salary to be for a candidate with 2 internships compared to none (holding other factors constant)? (3 points) e) Using the testData and models model1 (2a), model2(2b), model3 (2d), predict ‘starting_salary_usd’ for each row in testData. Calculate the precision measure for each model’s predictions. (6 points)i) Which model performed the best according to the value of precision measure? (2 points)ii) Interpret the precision measure value of model1 in the context of prediction accuracy. (2 points)

Fnet = ma Ff = FN