C207 OA WGU Questions with 100% Correct Answers

C207 OA WGU Questions with 100% Correct Answers Simple indexing -Answer-Common analytic measure to improve performance. Compares current data with data during a base period. (Price / Price during "Base Period") x 100 i.e. Big Mac was 1.60 in 1968 which is base period. what is index for 2014 if price was 4.80 then? (4.80 / 1.60) * 100 = 300 (means price is 3x greater than base period) Used to identify price fluctuations of supplies, materials, products, etc. Weighted Index -Answer-assign a weight to allow for significant differences in the index. Reasons for including analytics in decision-making -Answer-decrease cost of data storage increase processing power Descriptive Analytics -Answer-using current and past data for strictly descriptive purposes. i.e. car price data shows a 2% increase over the prior year a manager wants to know why sales spiked during the prior quarter Predictive / Inferential Analytics -Answer-using current and past data to predict/estimate future. i.e. based on the past 10 years of data for car prices, we predict an increase of 1.5% over the upcoming year. Prescriptive Analytics -Answer-using past data to PREDICT or ESTIMATE future in order to optimize operations includes experimental design and optimization to aid in DECISION-MAKING. MANAGERIAL DECISIONS. i.e. based on past data, sales prices for electric cars could increase by 5% if we increased charging stations by 7% Big data -Answer-Data so big that it's difficult to process using traditional methods. Stored in a Data Warehouse. Mined to identify patterns and trends Primary purpose is to encourage buying behavior. Enables products to be more tailored to customer base. Improves decision-making. Supports development of next generation products/services. watch for keywords in test options. i.e. company TOTAL sales (just one number) vs all sales invoices Structured / Quantitative Data -Answer-Data follows pre-defined formats. i.e. multiple choice answers, addresses, names, stock tickers Unstructured / Qualitative Data -Answer-Data doesn't follow pre-defined formats. Usually gets structured by a "theme analysis" i.e. blocks of freeform text, audio, video Continuous Data -Answer-Data that can take any value (within a set range) i.e. 3.14159, -189,115.2 a thermometer reads 66.5 degrees Interval Data (data measuring levels) -Answer-data is ordered at equal intervals apart and "0" doesn't mean absence of data, just another data point a type of continuous data i.e. date, time, degrees Ratio Data (data measuring levels) -Answer-0 actually means nothing, not just a data point a type of continuous data i.e. money, height weight Discrete Data -Answer-Data that can only take on whole values and has clear boundaries i.e. 4, 7, 8 in a preset range of 1-100 Ordinal data (data measuring levels) -Answer-data is ordered based on quality a type of discrete data i.e. in blackbelt data, level "3" is higher quality than "1" gold, silver, and bronze medals Nominal / Categorical Data (data measuring levels) -Answer-data is assigned a category/label for identification and grouping purposes a type of discrete data i.e. males are assigned "0" and females "1" potential quality errors: categories can be misspelled Attribute Data -Answer-Data that shows whether a result meets a requirement or not (yes/no, pass/fail). Davenport-Kim Three-Stage Model -Answer-1. Frame the problem - recognize problem and review previous findings. 2. Solve the problem - modeling, collection, analysis 3. Communicate results - tailor to audience, use visuals, show results. Reliability of Data -Answer-data that is consistent (but not necessarily accurate) i.e. a thermometer reads 20, 21, 21, 20, 20, 19, 19, 21, 20, 19 a test given to a student consistently shows similar scores Validity of Data -Answer-data that is accurate requires sample selection to be adequate size and random. i.e. a thermometer consistently reads from 20-25 F but the water isn't even frozen (not valid) Data Error Types -Answer-Omission - data being left out, missed, forgotten. sorting in spreadsheet can help to identify Out of Range - data that doesn't fit the expected, viable range. sorting in spreadsheet can help to identify outliers. Entry/input errors - typos, miscommunications, illegible handwriting Systematic Error -Answer-error will cause other errors until fixed i.e. a tire pressure sensor breaks and stops functioning, resulting in omission errors until fixed a scale is calibrated prior to being used in order to reduce systemic error Random Error / Unpredictable Error -Answer-error that does not consistently repeat due to system flaw and therefore doesn't need fix/adjustment. aka its "self fixing". minimize effects by increasing sample size i.e. a tire pressure sensor records an outlier / out-of-range caused by going over a speed bump at high speed True Score Theory -Answer-Observed Score (raw data score) = true score + random error score + systematic error in absence of systematic error, it's just true score + random error Measurement Bias -Answer-data doesn't represent the s