How does the data science methodology ensure continuous improvement?1 pointBy automating the entire processBy incorporating feedback and making adjustmentsBy only relying on expert opinionsBy making the methodology linear and rigid

Which of the following statements describes how data scientists refine the model after the initial deployment and feedback stages?1 pointBy collecting more data from controlled groups.By automating the intervention program.By incorporating information about participation and possibly refining with detailed pharmaceutical data.By conducting a complete overhaul of the model.

Question 4What is a method for examining and evaluating how a process works currently in order to get to an improved future state?1 pointData-driven decision-makingFive whysGap analysis Root cause analysis

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

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

What tasks may occur during the ask step of the data analysis process? Select all that apply.1 pointCommunicate with stakeholdersProperly maintain a databaseUse the five whysDetermine whether something needs to be fixed