Which statement best describes the Modeling Stage of the data science methodology?1 pointModeling always uses training and test setsThe Modeling stage is followed by the Analytic Approach stageModeling always requires testing multiple algorithms and parametersModeling is always based on predictive model

Select the three correct statements about the Evaluation stage of the data science methodology. 1 pointModel Evaluation includes validating that the model is designed as intendedEvaluating the data model includes ensuring that the model processes the data s as intendedModel Evaluation always includes statistical significance testingModel Evaluation ensures the data are correctly handled and interpret

Question 2Which of the following statements represents the essential characteristics of the data science methodology?1 pointData Science Methodology is a highly iterative process. At any point in the methodology, data scientists can decide to repeat a stage or revisit a prior stage and work forward from that previous stage.Data Science Methodology stages and work ends immediately ends when the data scientist deploys the model.Data Science Methodology has no endpoint because data collection occurs before identifying the data requirements.Data Science Methodology stages immediately end after data scientists deploy the code because no feedback is required

Question 3For predictive models, a test data set, which is similar to but independent of the training set, is used to determine how well the model predicts outcomes—using a training or test. A test data set happens during which stage in Foundational Data Science Methodology?1 pointAnalytic Approach.Data Requirements.Model Evaluation.Deployment

The final stages of the data science methodology are an iterative cycle between which stages?1 pointModeling, Deployment, Data Understanding, Data PreparationModeling, Evaluation, Deployment, and FeedbackData Understanding, Data Preparation, Evaluation, and FeedbackData Preparation, Evaluation, Feedback, Deploymen

Select the correct statement about the Data Preparation stage of the data science methodology.1 pointThe Data Preparation stage involves handling missing and improperly coded data and can include using text analysis to structure unstructured or semi-structured text dataThe Data Preparation stage cannot be accelerated using automationThe Data Preparation stage is typically the least time-consuming methodological stepData scientists only use feature engineering when manually preparing the data