Business Research Methods Study Set 5

Business

Quiz 15 :

Data Preparation and Description

Quiz 15 :

Data Preparation and Description

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Data entry followed data collection in the research profiled during the opening vignette. What concerned Jason about this process
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Jason was concerned that using untrained data entry personnel, especially those who had been treated for mental problems, would introduce an unacceptably high rate of error into the data entry process.

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Which data preparation process was Jason doing during data entry
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Jason was taking entered data and comparing it to the original questionnaire. Therefore, he was performing a data analysis.

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Choose one of the cases from the text website that has an instrument (check the Case Abstracts section for a listing of all cases and an abstract for each). Code the instrument for data entry.
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A problem facing shoe store managers is that many shoes eventually must be sold at markdown prices. This prompts us to conduct a mail survey of shoe store managers in which we ask, "What methods have you found most successful for reducing the problem of high markdowns " We are interested in extracting as much information as possible form these answers to better understand the full range of strategies that store managers use. Establish what you thin are category sets to code 500 responses similar to the 14 given below. Try to develop an integrated set of categories that reflects your theory of markdown management. After developing the set, use it to code the 14 responses. a) Have not found the answer. As long as we buy style shoes, we will have markdowns. We use PMs on slow merchandise, but it does not eliminate markdowns (PM stands for "push-money"… special item bonuses for selling a particular style of shoe.) b) Using PMs before too old. Also reducing price during season. Holding meetings with salespeople indicating which shoes to push. c) By putting PMs on any slow-selling items and promoting same. More careful check of shoes purchased. d) Keep a close watch on your stock, and mark down when you have to. That is, rather than wait, take a small markdown on a show that is not moving at the time. e) Using the PM method. f) Less advance buying… more dependence on in-stock shoes. g) Sales… catch bad guys before it's too late and close out. h) Buy as much good merchandise as you can at special prices to help make up some markdown. i) Reducing opening buys and depending on fill-in service. PMs for salespeople. j) Buy more frequently, better buying, PMs on slow-moving merchandise. k) Careful buying at lowest prices. Case on the buying line. Buying closeouts, FDs, overstock, "cancellations." (FD stands for factory-discontinued style.) l) By buying less "chanceable" shoes. Buy only what you need, watch sizes, don't go overboard on new fads. m) Buying more stable merchandise. Buying more from fewer lines. Sticking with better nationally advertised merchandise. n) No successful method with the current style situation. Manufacturers are experimenting, the retailer takes the markdowns-cuts gross profit by about 3 percent-keep your stock at lowest level without losing sales.
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Select a small sample of class members, work associates, or friends and ask them to answer the following in a paragraph or two: "What are your career aspirations for the next five years " Use one of the four basic units of content analysis to analyze their responses. Describe your findings as frequencies for the unit of analysis selected.
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Define or explain: a) Coding rules b) Spreadsheet data entry c) Bar codes d) Precoded instruments e) Content Analysis f) Missing data g) Optical mark recognition
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How should the researcher handle "don't know" responses.
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Simplement, Inc., which provides data sourcing solutions for Systems Applications and Products (SAP) customers, announced the achievement of subsecond response times for discovery and exploration in billion row datasets involving sales data collected in the sales and distribution module of SAP. Business users employing technologies like Microsoft Excel and Tableau can immediately explore and visualize supersized data sets leading to higher productivity and more meaningful insights. What other applications would you recommend to your organization, particularly marketing or IT staffs
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