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Exam Guide Mid Term Arizona State University - WPC 300

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WPC 300 – Mid Term Exam Study Guide  Discuss what makes analytics science o Defining characteristics of science – Questioning, Exploring, Observing, Comparing, Measuring, Experimenting, Discovering. o Facts (evidenc ...

WPC 300 – Mid Term Exam Study Guide  Discuss what makes analytics science o Defining characteristics of science – Questioning, Exploring, Observing, Comparing, Measuring, Experimenting, Discovering. o Facts (evidence) – Irrefutable piece of information. Not an opinion. o Falsification o Parsimony – Preferring the simpler answer over the more complicated in-depth answer. o Etc.  Different analytical modeling techniques, be able to understand what is the best analytical technique for different business scenarios. o Descriptive – Why, How, When, did this happen? Based on the past. o Predictive – Predicting what will happen based on what happened in the past. o Explanatory – Explaining why something occurred. o Prescriptive – Recommending action. Using all techniques.  Be able to design an experiment given a scenario o Golden standard – Randomized Double-Blind. o What does randomization mean? – Equal Chance. o Control group, treatment group – Control group, left alone and observed. Treatment group, intervened with. o Outcome measures – Our results. o A/B testing – Comparing two or more groups  Given a scenario, discuss to experiment or to observe. o Explain limitations of observations – Subject to confounding variables. o Explain strength of observations – Long periods of time. Ample amount of data. Easier. o Explain limitations of experiments – Harder to construct. Expensive. Short. o Explain strength of experiments – Clear data. Able to determine causation. Limits the possibilities of confounding variables.  Understand sampling from population o Why sampling – Not practical to study the WHOLE population. Sampling is more feasible with time and resources. o Sampling methods – Convenience sampling. Random sampling. Cluster sampling. o Sources of sampling biases – Response and non-response bias. How the questions is phrased. o Be able to discuss potential sampling biases given a scenario -  Understand group comparisons o Understand the concept of statistical significance - o Understand t values and p values - o Be able to compute t values -  Cluster analysis

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