70.000 60.000 50.000 40.000 30.000 Estimated Marginal Means
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- Suppose when you add flexibility to your model by adding higher-order terms or more predictor variables that you begin to see the test or validation error (MSE or SSE evaluated on the test or validation set) begin to increase away from the training error. What kind of a problem are your models experiencing?A medical researcher conducted an observational study to understand the recovery rate for patients infected with the COVID-19 in Malaysia. The researcher contacted thirteen COVID-19 survivors and interviewed them regarding their recovery experience. Two of the questions asked are the recovery period (in days) and the number of days that have passed since receiving the second dose of COVID-19 vaccine prior to infection. The recorded data is summarized as (at the image files). i) Identify the dependent variable in the study. ii) Calculate the correlation coefficient and interpret its value. iii) Estimate the regression model parameters and write the estimated linear regression model. iv) Based on your answer in iii), predict the recovery period if a person is infected with COVID-19 after 200 days of receiving second dose of COVID-19 vaccine. v) Table 1 represents the incomplete ANOVA table of the study. Find the values of P, Q, R and S. vi) Test the linearity between the two variables…Calculatelog_10(5)
- Employee’s human capital is measured in terms of his/her age, education, tenure, and rank. Number of years an employee worked in the same organization measures the amount of firm-specific human capital that employee possesses. Data of 413 employees’ tenure was analyzed to predict interim leadership role importance in a study reported in Journal of Advanced Management Research (Vol. 9, 2012). The following table shows the data of these employees tenure in the organization: Tenure (in years) 0-1 1-6 6-11 11-20 20-21 No. of employees 48 109 58 75 123 Calculate mean tenure of these 413 employees.What measures of fit are typically used to assess binary dependent variableregression models?Consider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certain
- PLE collects a variety of data from special studies, many of which are related to the quality of its products. The company collects data about functional test performance of its mowers after assembly; results from the past 30 days are given in the worksheet Mower Test. In addition, many in-process measurements are taken to ensure that manufacturing processes remain in control and can produce according to design specifications. The worksheet Blade Weight shows 350 measurements of blade weights taken from the manufacturing process that produces mower blades during the most recent shift. Elizabeth Burke has asked you to study these data from an analytics perspective. Drawing upon your experience, you have developed a number of questions: For the mower test data, what distribution might be appropriate to model the failure of an individual mower? What fraction of mowers fails the functional performance test using all the mower test data? What is the probability of having x failures in the…The subsets of {1,2} are Φ, {1}, {2} and {1,2}. So there are four possible potential models when deciding on a regression with a choice of inputs from a dataset containing two potential input variables. Your friend tells you this is nonsense and there are three possible models because the empty set Φ is just an imaginary concept concocted by some mathematician. What should you say to your friend? You should explain that the empty set corresponds to the model y = β + ε, where β is some constant and ε is a residual term. In this model, the output predictions are always equal to the output's sample average. You should explain that the empty set corresponds to the model y = ε, where ε is a residual term. In this model, the output predictions are totally random. You should indeed agree. Your friend is spot on and one cannot have a regression with no input variables. You should partially agree. Your friend is spot on that there are three models and not…In a snow geese feeding trial, a model was constructed relating gosling** weight change (Y), to digestion efficiency (X1) which is measured on a scale from 1 to 10, depending on how well nutrition is absorbed by the goosling, and diet (either plants or duck chow). Using Bi, etc. to represent the coefficients of independent variables, and defining any independent variables you create and use, write out the following: [WRITE OUT THE FULL MODELS IN SINGLE EQUATIONS IN EACH SECTION BELOW, NOT BROKEN DOWN INTO SEPARATE SUB-EQUATIONS] Define your independent variables here a) a first order model that allows for different intercepts but the same slope for each diet b) a first order model that allows for different slopes and intercepts for each diet (c) a first order model that allows for different slopes and the same intercept for each diet
- Beryllium is an extremely lightweight metal that is used in many industries, such as aerospace and electronics. Long-term exposure to beryllium can cause people to become sensitized. Once an individual is sensitized, continued exposure can result in chronic beryllium disease, which involves scarring of the lungs. In a study of the effects of exposure to beryllium, workers were categorized by their duration of exposure (in years) and by their disease status (diseased, sensitized, or normal). The results were as follows: Duration of Exposure <1 1 to <5 ≥5 Diseased 14 13 18 Sensitized 11 20 15 Normal 78 140 209 Test the hypothesis of independence. Use the a=0.10 level of significance and the P-value method with the TI-84 Plus calculator. What do you conclude? State the null and alternate hypotheses.5