An insurance company has past data that will allow them to build a model to predict if a newly filed insurance claim is fraudulent. The outcome variable is "fraud" (yes or no), and there is a combination of quantitative and categorical predictor variables. Which are appropriate methods that can be used to predict which newly filed insurance claims are fraudulent?
A multiple linear regression model is appropriate for this data, but logistic regression is not
A logistic regression model is appropriate for this data, but multiple linear regression is not
Both logistic regression model and a multiple linear regression models are appropriate methods for this data
Neither a logistic regression model nor a multiple linear regression model is appropriate for this data
Q. filed insurance claim is fraudulent. The outcome variable is "fraud" (yes or no), and there is a combination of quantitative and categorical predictor variables. Which are appropriate methods that can be used to predict which newly filed insurance claims are fraudulent?
Answer:-
Because predictor is binary we will use logistic regression we cannot use linear regression.we can make dummy variables for categorical data.
A logistic regression model is appropriate for this data, but multiple linear regression is not.
An insurance company has past data that will allow them to build a model to predict if a newly fi...
Decide (with short explanations) whether the following statements are true or false. e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary statisties z-10, s/-3 sy-5 and у-20. For a new data point with x = 13, it is possible that the predicted value is y = 26. f A standard multiple regression model with continuous predictors and r2, a categorical predictor T with four values, an interaction between a and...
Need help with stats true or false questions Decide (with short explanations) whether the following statements are true or false a) We consider the model y-Ao +A(z) +E. Let (-0.01, 1.5) be a 95% confidence interval for A In this case, a t-test with significance level 1% rejects the null hypothesis Ho : A-0 against a two sided alternative. b) Complicated models with a lot of parameters are better for prediction then simple models with just a few parameters c)...
Please use DataAnalysis A study was conducted to build a regression model to predict miles per gallon (MPG) of vehicles. To develop the model, you obtained MPG of 43 random vehicles. In addition, you collected the following information - Length: vehicle length (inches) - Width: vehicle width (inches) - Weight: vehicle weight (pounds) - Made in Japan: whether the car is manufactured in Japan or not a. Fit a multiple regression model using all four independent variables. For "made in...
The director of a training program for a large insurance company has the business objective of determining which training method is best for training underwriters. The three methods to be evaluated are classroom, online, and courseware app. The 30 trainees are divided into three randomly assigned groups of 10. Before the start of the training, each trainee is given a proficiency exam that measures mathematics and computer skills. At the end of the training, all students take the same endof-...