Group A has a mean of 0 and a median of 15 What is most likely true?   Question 8 options:   Group A likely has a high outlier or right skew   Group A is likely roughly symmetric and unimodal   Group A likely has a low outlier or left skew   Group A likely has low and high outliers.   None of these In descriptive statistics, we are trying to determine what model fits our situation best.   Question 12 options:   True   False

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Investigators evaluated the effect of education (E1-1 if college or more, E2=1 if Masters degree or more, E1-E2=0 if less than college), Mother's Education (M=1 if college or more, O otherwise), and age (A, continuous, in years) on employment status (yes/no) using the following Logistic regression model: Logit= a + B1 E1+B2*E2 + B3*A + B4*M + B5*A*M SAS was used to create the following estimates: a= -2, B1-0.2, B2-0.4, B3-0.1, B4-0.3, B5=0.02. Calculate the odds that a 25 year old with just a college degree whose mother had a college degree is employed. Enter the odds to three decimal places.

2. Take a bivariate normal distribution with two random variables X and Y, with mean value = (1, -1), var(X) = 3, var(Y) = 6, and cor(X,Y) = -0.5. %3! (a) create a contour plot for this data (b) plot 1,000 simulations of this distribution (c) Using 1,000,000 simulations, find (1) the expected value of Y (ii) the expected value of Y, given that X> 2 (ii) the expected value of Y, given that X = 2

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D Question 10 Suppose that you are using a [support, confidence, lift] framework to analyze whether the strong association rule AB is interesting. Which conclusion would you make if the data obtained were A B [20%, 80%, 0.7]? ✓ [Select] The occurrence of A likely leads to the absence of B The occurrence of A likely leads to the occurrence of B There is likely no association between A and B • Previous

In this section we create the model object and define the loss function and optimizer. For the loss function use nn.CrossEntropyLoss() instead of the mean-squared loss done in class. Use the same optimizer as in class.   learning_rate = 0.001 num_epochs = 5 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") #this is to use gpu if available   # **create your neural net model here, call the variable 'model'** # ** complete following lines of code to define loss function and optimizer #criterion = **complete this** #optimizer = **complete this**

The price of a certain combo meal at different franchises of a national fast food company varies from $5.00 to $17.38 and has a known standard deviation of $2.13. A sample of 29 students in an online course that includes students across the country stated that their average price is $5.75. The students have also stated that they are generally unwilling to pay more than $6.50 for this meal. Formulate and conduct a hypothesis test to determine if you can conclude that the population mean is less than $6.50. Use a level of significance of 0.05. Is there sufficient evidence at the 0.05 level of significance that the population mean is less than $6.50? Determine the null hypothesis, Ho, and the alternative hypothesis, H,. Họ: H 6.50 < 6.50 (Type integers or decimals. Do not round.) Compute the test statistic. - 1.90 (Round to two decimal places as needed.) Find the p-value for the test. (Round to three decimal places as needed.)

Question 1: Suppose that a Naive Bayesian classifier is created using a given training data set. Then, predictions are made on several testing points using this classifier. The predicted positive class probabilities and the actual class labels for these testing points are shown as follows. Please draw the ROC curve for the above prediction. Please clearly denote your splitting values and show the TP, FP, TN, FN, TPR, FPR values at each splitting value.   Sample ID Actual Class Label Predicted Positive Class Probability 1 - 0.1 2 + 0.3 3 - 0.4 4 + 0.4 5 + 0.6 6 + 0.8