BUAL 2600 EXAM 1 QUESTIONS AND ANSWERS WITH COMPLETE SOLUTIONS

BUAL 2600 EXAM 1 QUESTIONS AND ANSWERS WITH COMPLETE SOLUTIONS 5.0 (1 review) Business Analytics A process of transforming data into action through analysis and insights in the context of organizational decision making and problem solving 3 types of analytics users Business user, Business analyst, and Data scientist Data Scientist A person skilled in all areas (programming, statistics, mathematics, data visualization, data analysis, and computer science Business Analyst A person who manages, cleans, and aggregates data; finds a solution to change business processes Business User Someone who uses the data to perform their job Analytics Process 1. Identify your problem 2. Collect Data 3. Descriptive Analytics 4. Predictive Analytics 5. Prescriptive Analytics 6. Ask another question Descriptive Analytics Describes what has happened in the past and why it has happened Example 1: Admissions Process Which high schools provide the highest percentage of successful applicants? What has been the average high school GPA from each size of high school? What has been the average ACT or SAT score among successful applicants? Example 2: City Trash Pickup How has the city picked up trash in the past? Given the sensor data from receptacles, which receptacles are ready for pick up? Where are the receptacles that are ready for pick up? How long does it take to complete pickup? Predictive Analytics Focuses on the historical data to predict what MIGHT happen in the future Example 1: Admissions Process Based on data from a future applicant would the university accept him or her? That is, can the university predict that this applicant would be able to graduate in five years or less? Example 2: City Trash Pickup Can we feed data from trash receptacles each evening into a navigation system on each truck to minimize the distance driven? Prescriptive Analytics Goes beyond recommending courses of action by identifying likely outcomes of each decision Example 1: Admissions Process Where might university recruiters choose to visit? What areas would the university target in their marketing and advertising campaigns? Example 2: City Trash Pickup Can we reduce the number of trucks needed for trash pickup in the city? Quantitative Data Has measurable values, numerical quantities, units, and can be mathematically analyzed. Can be discrete (whole numbers) or continuous (any value including decimals) Qualitative Data Can be categorized or counted. Can be structured (organized into relational databases, ex. address, phone number, etc) or unstructured (dumped into one big database, ex. photos, videos, posts) Examples: yes or no questions, zip codes and area codes Data Quality Accuracy, integrity, consistency, completeness, timeliness Types of Data Collection Point of Sales Systems, clickstream data, social media data, sensor data, surveys, experiments, observations, interviews Population The set of all objects, items, or individuals that pertain to a business problem Sample Part of a population that information is actually collected from Nonprobability Sampling The probability of selection for each element from the population is unknown. Voluntary and Convenience sampling Convenience Sampling We elect each element of the population because it is easy to obtain Bias: surveyor targets people who are convenient, not so random Voluntary Sampling Participants volunteer to provide data Bias: people who volunteer typically have strong opinions Probability Sampling Allow us to make unbiased inferences about the population because the process ensures that every element of a population has the same probability of being chosen. There are four probability random sampling methods: simple random, cluster, systematic, and stratified Simple Random Sampling Completely random sample Cluster Random Sampling First the population is divided into groups that share common characteristics, then randomly selected some of the groups (sample is everyone in the group)