DSCI: Exam 1 Questions With All Complete And Verified Solutions.

Describe the quantitative analysis approach - correct answer -the process of analyze information to make final decision. Include unpredictable things that affect the decision-making process (weather, state, federal legislation Understand the application of quantitative analysis approach in real situation. The 7 step of QA approach: - correct answer +Define the problem +Develop a model +Acquire input data +Develop a solution +Test the solution +Analyze the results +Implement the results. Possible problem in using quantitative analysis - correct answer +Expensive and time consuming to develop and test. +misused and understood because of complexity. +downplay the role and value of non quantifiable information. +oversimplify variable of the real world. 6 steps of decision making process - correct answer 1. State the situation 2. List the options 3. Weigh the possible outcomes 4 List payoffs for each state of decision alternative combination 5. select one of the decision theory models 6. Apply the model and make decision 3 Types of decision making environment - correct answer +Decision making under certainty: decision maker knows the consequence of every alternative or decision choice. +Decision making under risk: decision maker knows the probabilities of various outcomes. +Decision making under uncertainty: decision maker does not know the probabilities of various outcome. DMUU terms: Maximax Maximin Equally likely Criterion of realism Minimax - correct answer +Maximax: find the alternative that maximizes the maximum payoff. +Maximin: alternative with maximum minimum output. +Criterion of realism: weighted average based on optimism of the future. +Equally likely: assume all state to be equally likely, choose maximum average. +Minimax: alternative that minimize the maximum opportunity loss. Regression analysis What is the role if dependent and independent variable? - correct answer -use to understand the relationship between variables and predict values. -dependent: response and, independent: predictor What to evaluate to see how well the model predicts the response variable? +The variability in the Y variable +Coefficient of determination +Correlation coefficient - correct answer +The variability in the Y variable SST: total variability about the mean SSE: variability about the regression line SSR: variability that is explained +Coefficient of determination: the proportion of the variability in Y. +Correlation coefficient: measures the strength of the linear relationship 4 Assumption of the regression model: - correct answer +Error are independent +Errors are normally distributed +Error have a mean of zero +Errors have a constant variance Residual Analysis 3 type of plot and state if they violate the regression model: - correct answer -Highlight glaring violations of the assumptions +Healthy residual plot- no violations +Nonlinear residual plot-violation +Non Constant error residual plot-violation