Background The dataset includes 9 baseline numeric variables: age, body mass index, average blood pressure, and six blood serum measurements for each of n = 442 diabetes patients. The response of interest is a quantitative measure of diabetes disease progression one year after baseline. The dataset is obtained from sklearn.datasets. We will be fitting multiple linear regression models to the train dataset and making predictions on the test dataset. Attribute Information: age: age in years bmi: body mass index bp: average blood pressure s1: tc, total serum cholesterol s2: ldl, low-density lipoproteins s3: hdl, high-density lipoproteins s4: tch, total cholesterol / HDL s5: ltg, possibly log of serum triglycerides level s6: glu, blood sugar level Target: quantitative measure of disease progression one year after baseline (Response variable) Note: All features have NOT been standardized.

Question 6: Prediction – 9 points For this question, use the testData. Using testData and with the previously built models in Q2,3,5, predict the Target and output the average of these probabilities for each of the models below and summarize the results: i) Full linear regression model from question 2b (model1) ii) Reduced model from question 2b (model2) iii) Stepwise forward model from question 3a (forward_model) iv) Stepwise backward model from question 3c (backward_model) v) Stepwise forward-backward model from question 3f (both_model) vi) Ridge regression model from question 5a (ridge.model) vii) Regular Lasso model from question 5c (lasso.model) viii) Group Lasso model from question 5f (group_lasso) ix) Elastic Net model from question 5i (enet.model)

BONUS (up to 3 points): Explain the similarities and differences between osteomalacia and rickets.

As a consequence, a punisher is a stimulus, event, or activity that:  

A spring is attached to the hook of the iolab. The following data is collected showing the spring force (in N) on the vertical axis plotted as a function of position on the horizontal axis (in meters).  From this data, determine the equilibrium position of the spring (approximately). In case you find it hard to read the summary statistics on the right, the slope of the best fit line is approximately -2 and the intercept is approximately 0.4. 

Question 4: Full Model Search – 8 points For this question, use the trainData. How many models can be constructed using subsets drawn from the full set of variables? (2 points) Compare all possible models using Mallow’s Cp. Display the variables included in the best model and the corresponding Mallow’s Cp value. (2 points) Use the selected variables from Q4b to fit another multiple linear regression model, call it best_model. Display the model summary. (2 points)’ Compare the models (model1, model2, forward_model,backward_model, best_model, both_model) using Adjusted R^2 and AIC. Which model is preferred based on this? (2 points)

Two masses are connected as shown in the figure. In this question, the numbers will not be needed. The system is released from rest and mass A falls to the floor through a distance of 1 m. The rope and pulley are massless. The pulley is frictionless and the table is frictionless.  MODEL: You decide to model this problem by taking the system to be the Earth and mass A only. You take the gravitational potential energy to be 0 at the floor.  Which of the following energy diagram is a good visualization of the “before and after” given the system chosen?  Before is shown in the figure and the after is after block A falls 1 m just before it hits the floor.     

Manipulating ______________________ was one way to meet the characteristic of “focus on reinforcement first” designed to influence the effectiveness of a punisher.  

A _____________ schedule is often used to study choice behavior.  

If effective, which of these is most clearly an example of positive punishment for a child hitting a sibling?