6. We ran a Vector-autoregresive model with five variables: with dtrade (change in trade balance), drex (change in real exchange rate), diipuk (change in Index of UK Industrial production), diipus ((change in Index of US Industrial production) and doilpr (change in Index of Oil price Index) and the result for lag length selection is as follows: Lag 1 2 3 Log-Likelihood 4397.98 4547.56 4591.56 4610.42 4630.33 p-values for Log-Likelihood Ratio Test 0 0 0.049 0.03 AIC -21.2735 -21.8768 -21.9688 -21.6308 -21.5098 SBC -21.2248 -21.5845 -21.433 -21.1597 -20.8915 Which model should you choose based on different criteria and why?

You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “State Island”). Write down the population model that will properly test the effect of 3-way interaction between AGE, MSS, and BOROUGH on BW.

You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “State Island”). Write down the population model that will properly test the effect of 3-way interaction between AGE, MSS, and BOROUGH on BW. THIS IS A 3 WAY INTERACTION BETWEEN THIS THREE PREDICTORS. Attached is an example.

You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time.The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). How many dummy variables do you need to create to analyze the effect of MSS? Select “Non-smokers” as a reference category. Write out all the dummy variables.

A linear regression to quantify the salaries of the employees in a company is estimated, using the following variables: Y: the salary of the employee in 1000 SEK. Age: the age of the employee in years R: the categorical variable Education with 3 groups; Primary, Secondary, University. a)Write down a linear model with intercept for the variable Y based on Age and R, in which the Primary level of education is the reference category for the Education variable. b)Mention a test to see if the variable Age significantly improves the model fit?

A company provides maintenance service for water-filtration systems throughout southern Florida. Customers contact the company with requests for maintenance service on their water-filtration systems. To estimate the service time and the service cost, the company's managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors, the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performed the service. Data for a sample of 10 service calls are reported in the table below. Repair Timein Hours Months SinceLast Service Type of Repair Repairperson 2.9 2 Electrical Dave Newton 3.0 6 Mechanical Dave Newton 4.8 8 Electrical Bob Jones 1.8 3 Mechanical Dave Newton 2.5 2 Electrical Dave Newton 4.9 7 Electrical Bob Jones 4.6 9 Mechanical Bob Jones 4.8 8 Mechanical Bob…

A company provides maintenance service for water-filtration systems throughout southern Florida. Customers contact the company with requests for maintenance service on their water-filtration systems. To estimate the service time and the service cost, the company's managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors, the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performed the service. Data for a sample of 10 service calls are reported in the table below. Repair Time Months Since in Hours Last Service 2.9 3.0 4.8 1.8 2.5 4.9 4.2 4.8 4.4 4.5 2 6 8 3 2 7 9 8 4 6 Type of Repair Repairperson Electrical Mechanical Electrical Mechanical Electrical Electrical Mechanical Mechanical Electrical Electrical Dave Newton ŷ = X Check which variable(s)/term(s) should be in your…

You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”) Questions: (1) How many dummy variables do you need to create to analyze the effect of BOROUGH and MSS? Select “Manhattan” and "Non-Smoker"  as a reference category. Write out all the dummy variables. (2) Write down the population model that estimates BW based on variables AGE, MSS and BOROUGH. Make sure that it is clear what each predictor means. (3) How many parallel lines are computed by model from 1i)?

A researcher is studying the intensity of hurricanes that entered the Gulf of Mexico between 1975-2015 and the average water temperature of the Gulf of Mexico at the hurricane's peak strength. What is the independent and dependent variable in this study?

Assume we have data demonstrating a strong linear link between the amount of fertilizer applied to certain plants and their yield. Which is the independent variable in this research question?