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BQA Midterm Exam Questions and Answers|Latest Update

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BQA Midterm Exam Questions and Answers|Latest Update Analysis tools: Step 3 Data Analysis select and apply the most appropriate statistical/analytical methods for each digestible question develop useful/appropriate robust analysis Decisions: Step 4 Decision Making Integrate answers of multiple digestible questions to address a complex decision-making problem faced by the firm provide multiple scenarios iterate step 2 through step 4 if needed

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BQA Midterm Exam Questions and
Answers|Latest Update

Analysis tools: Step 3 Data Analysis


select and apply the most appropriate statistical/analytical methods for each digestible question


develop useful/appropriate robust analysis




Decisions: Step 4 Decision Making


Integrate answers of multiple digestible questions to address a complex decision-making

problem faced by the firm


provide multiple scenarios


iterate step 2 through step 4 if needed




Why do we use Statistical Models? Functional Relation: y= f(x)


Statistical Relation: y1 = b0 + b1x1 +ei


Causes of variation that are based on random reasons that we cannot identify


Prediction VS. reality: the error represents the difference between the actual observation versus

the predicted observation.

, Data Set a collection of data that could consist of items such as marketing survey

responses, historical stock prices, or a collection of measurements related to a manufactured

item




Database a collection of related files containing records on people, places, or things that

are usually arranged in a two-dimensional table where columns correspond to an individual

data item and rows represent individual records




Database Analytics: 3 step process Identify the right values


Data reduction


Data validation




Identifying the Right Values: Step 1 with every increasing amount of data, you should be

ensuring that the data for your models reflects your target demographics and maximizes

profitability




Data Reduction by reducing the amount of data, you focus your analysis on the most

important data points. This reduces the chance that outliers may bias your results.

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