Compute the least-squares regression line for predicting the diastolic pressure from the systalic pressure. Round the wope and y-intercept to at least four decimal places. Regression line equation: y =

Consider the following growing network model in which each node i is assigned an attractiveness a¿ € N+ drawn from a distribution π(a). Let N(t) denote the total number of nodes at time t. At time t = 1 the network is formed by two nodes joined by a link. - At every time step a new node joins the network. Every new node has initially a single link that connects it to the rest of the network. - At every time step t the link of the new node is attached to an existing node of the network chosen with probability II; given by where Z = Ili = ai Z' Σ aj. j=1,...,N(t−1)

1. Suppose that a set of samples x1, x2, ..., xn, all real numbers, are drawn i.i.d. from the same distribution. Also assume that this distribution is a Gaussian distribution, which can be represented as N(u, o²). Write a function that accepts a set of samples and returns the MLE estimator for u. NOTE: The code below will be evaluated by a Python 2.7 interpreter. def mle(samples): pass Run Reset Once your function is correct, your will receive a submission code that you should input into the answer field. Enter answer here 2. In the previous question, you were asked to write a function for an estimator of a parameter of a distribution. Is the result of this function, an estimator, a random variable? Yes No

You trained the regression model with 100 regressors and 1000 observations in the training and another 1000 in the test sample. You found that in-sample R2 over the training sample is 70% and the out-of-sample R2 over the test sample only - 30%. (select all that apply) a) Do you think there is any problem and how would you characterize it? Can adding more regressors (if you have them) help the model? b) Which approaches you may use to solve the problem? c) What would you expect the in-sample R2 to increase or decrease after that? What about the out-of-sample (test) R2?

When and why do we employ the Binomial, Poisson, and Proportional models of regression?

consider the following model: y = b_0+ b_1*x what is the parameter b_0? O a. the slope coefficient. O b. O C. O d. The independent variable. the dependent variable. the intercept.

You are given the true labels and the predicted probabilities from logistic regression model for N test examples. Approximately compute the AUC scores for ROC and PR curves.

Mary: "Before we run the multivariate linear regression, feature scaling should be performed." Give one reason to support Mary's idea. Moreover, should we perform feature scaling before or after the gradient descent?

In the simple linear regression equation ŷ = bo + b₁x, how is b₁ interpreted? it is the change in that occurs with a one-unit change in y O It is the estimated value of ŷ when x = 0 O It is the change in ŷ that occurs when bo increases O it is the change in ŷ that occurs with a one-unit change in

An instructor who taught two sections of engineering statistics last term, the first with 25 students and the second with 40, decided to assign a term project. After all projects had been turned in, the instructor randomly ordered them before grading. Consider the first 15 graded projects. (a) What is the probability that exactly 10 of these are from the second section? (Round your answer to four decimal places.)   (b) What is the probability that at least 10 of these are from the second section? (Round your answer to four decimal places.)   (c) What is the probability that at least 10 of these are from the same section? (Round your answer to four decimal places.)   (d) What are the mean value and standard deviation of the number among these 15 that are from the second section? (Round your mean to the nearest whole number and your standard deviation to three decimal places.) mean projectsstandard deviation projects (e) What are the mean value and standard deviation of…