WGU C207 Data Driven Decision Making Exam Prep Questions And Answers Graded A+

WGU C207 Data Driven Decision Making Exam Prep Questions And Answers Graded A+ A city government is trying to determine the national origins of its recent immigrant population. If a survey of the immigrant population is conducted in English what type of error might be present in the data? Omission Error An Educator develops a new standardized test to measure math skills of ninth graders. She has students in her home state of Ohio take the test. If the test is to be used on a national level, what type of error might be found in her data? Measurement Bias Process of turning data or information into knowledge. Analytics 3 Types of Analytics descriptive, predictive, prescriptive Descriptive Analytics What has happened in the past? Predictive Analytics What will happen in the future based on what has happened in the past? Or looks at one the impact of one variable on another. Prescriptive Analytics Decision models that indicate the best course of action Types of Descriptive Analytics: 1.Graphical Analysis (Histogram, Run chart, scatter, Pareto) 2.Discovery of patterns (sums, averages, percentages) Types of Predictive Analytics 1.Models (Time series/trend, regression, statistical quality control) 2.Simulation Types of Prescriptive Analytics 1.Optimization Models 2.Simulation 3.Decision Analysis Optimization Models help make the best decision while subject to resource constraints (linear programming) Simulation: probability and statics to model uncertainty Decision Analysis: Develop on optimal strategy for making decisions (Decision tree) Big Data: structure or un structured data in large volumes that need manipulation to become meaningful; Analysis of big data requires a system of organization 3 Stages of Davenport-Kim Model to Quantitative Decision Making: 1. Frame the Problem 2. Solving the Problem 3. Communicating the results Frame the problem includes... 1. Identify the problem 2. review what we already know 3. Chose the model and how to collect Solving the Problem includes ... collect the data and analysis the data Communicating Results includes... Communicate outcomes and act on results 4 Levels/ types of measurement 1. Nominal 2. Ordinal 3. Interval 4. Ratio Nominal: No intrinsic order; Ex. Male or Females Names, labels, categories that contain only two either/or (ex. Color or eyes, Pass/fail) Ordinal: Has an intrinsic order; Ex. Levels of energy - low, med, high Categories according to some quality, non-numeric (Satisfaction level, top 10) Interval: Can be added and subtracted but not multiplied or divided Has an order and all objects have equal intervals; no natural zero point (you cannot compare) (Ex. Temperature, Women's dress sizes) Ratio: Has a true zero and can be manipulated in any way Has a unique zero point and can be compared (Ex. Age, income, prices) Cleaning and organizing a data set that are collected; vital step and good decisions rely on clean and valid data Data Management Data Management helps ensure that the data produced is the following 5 things: 1. Relevant 2. Complete 3. Accurate 4. Available 5. Timely Error that is Unknown and unpredictable changed in environment; can be minimized by large sample size Random error Error that is from instruments or experimental design; constantly occurs Systematic Error Error that occurs When action has not been taken or something is left out Omission Error Error that includes Observation points that are distant from other observations; can figure out if it is correct or incorrect Outliers A measure of the degree to which data leans towards one side Bias / Skewedness Bias that happens When the sample is not represented of the population Measurement Bias Bias that happens when the respondent or interviewer has agenda that is not the whole truth Information Bias Bias that happens when Respondents say what they believe the interviewer wants to hear Response Bias Bias that happens when a Surveyor is actively seeking a response Conscious Bias 3 Types of Bias Mitigation: 1. Blind Study 2. Double Blind Study 3. Triple Blind Study Triple Blind Study: Data Analyzer, Data gatherer, and participant are not told Double Blind Study: Data gatherer and participant are not told Blind Study: Participant is not told Qualitative Research: Exploratory research, Data no Characterized by Number Quantitative Research: Quantifies the problem by assigning numerical value; ability to use measurements and analytics 3 Elements to Experimental Study Experimental Units Treatments Responses The effect of said treatments on the units; Measure of performance Responses Procedure being applied to each study Treatments Objects being observed Experimental Units Responses: The effect of said treatments on the units; Measure of performance A local school board is studying the impact of a proposed change in testing on math scores. Bias can be introduced into the study by both students and teachers. Which research technique would eliminate this type of bias? Double blind study What level of measurement are women's dress sizes (2,4,6, etc.)?