BUSINESS DATA ANALYTICS Assignment: Jamie received 105 responses, which are given in the Excel file Drout Advertising Survey. Review the questionnaire and classify the data collected from each que

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BUSINESS DATA ANALYTICS

Assignment:

Jamie received 105 responses, which are given in the Excel file Drout Advertising Survey.

  • Review the questionnaire and classify the data collected from each question as categorical, ordinal, interval, or ratio.
  • Next, explain how the data and subsequent analysis using business analytics might lead to a better understanding of stereotype versus empowerment advertising. Specifically, state some of the key insights that you would hope to answer by analyzing the data.
  • Use appropriate charts to visualize the data. Summarize the data using:

    • frequency distributions and histograms for numerical variables,
    • cross-tabulations, and
    • other appropriate applications of PivotTables

to break down the data and develop useful insights.

An important aspect of business analytics is good communication. Write up your answers to this case formally in a well-written report as if you were a consultant-File attached


Notes from professor:

Please develop YOUR OWN Business Data Analytics EXCEL models to support all your answers and analyses and post this(these) file(s) in addition to your Case Analysis Drout Advertising Research Project Report.

Finally, please answer ALL Questions and Sections of this Data Analytics for Business Case with great detail AND STEP BY STEP being extremely methodical and accurate in your answers. It is extremely important that for each Question and Section, you write the entire question and you LABEL and/or PLACE the appropriate headings and subheadings clearly for EACH part of the question and/or section.

BUSINESS DATA ANALYTICS Assignment: Jamie received 105 responses, which are given in the Excel file Drout Advertising Survey. Review the questionnaire and classify the data collected from each que
Structure of a Data Analysis Report A data analysis report is somewhat di erent from other types of professional writing that you may h ave done or seen, or will learn about in the future. It is related t o but not the same as: A typical psych /social science paper orgainzed around “intro /methods /analysis /results /discussion” sections. A research article in an academic journal. An essay. A lab report in a science class. The overall structure of a data analysis report is simple: 1. Introduction 2. Body 3. Conclusion(s) /Discussion 4. Appendix /Appendices The data analysis report is written for several di erent audiences at the same time: Primary audience: A primary collaborator or client. Reads theIntroduction and perhaps the Conclusion to nd out what you did and what your conclusions were, and the n perhaps shes/skims through the Body , stopping only for some additional details on the parts that he/she thought were interesting or eye-catching. Organize the paper around an agenda for a conversation you wa nt to have with this person about what you’ve learned about their d ata: e.g., from most general to most speci c, or from most important to least important, etc. Pro vide the main evidence from your analysis (tabular, graphical, or otherwise) in the Body to support each point or conclusion you reach, but save more detailed evidence, and other ancillary material, for t he Appendix . Secondary Audience: An executive person. Probably only skims theIntroduction and perhaps the ul Conclusion to nd out what you did and what your conclusions are. Leave signposts in the Introduction , Body and Conclusion to make it easy for this person to swoop in, nd the “headlines ” of your work and conclusions, and swoop back out. Secondary Audience: A technical supervisor. Reads theBody and then examines the Appendix for quality control: How good a job did you do in (raising and) answering the interesting questions? How e cient were you? Did you reach reasonable conclusions by defe nsible statistical methods? Etc. Make speci c cross-references between the Body and speci c parts of the Appendix so that this person can easily nd supporting and ancillary material rel ated to each main analysis you report in the Body. Add text to the technical material in the Appendix so that this person sees how and why you carried out the more detailed work shown in the Appendix . 1 The data analysis report has two very important features: It is organized in a way that makes it easy for di erent audiences to skim / sh through it to nd the topics and the level of detail that are of interest to them. The writing is as invisible /unremarkable as possible, so that the content of the analysi s is what the reader remembers, not distracting quirks or tics in the writ ing. Examples of distractions include: – Extra sentences, overly formal or owery prose, or at the oth er extreme overly casual or overly brief prose. – Grammatical and spelling errors. – Placing the data analysis in too broad or too narrow a context for the questions of interest to your primary audience. – Focusing on process rather than reporting procedures and ou tcomes. – Getting bogged down in technical details, rather than prese nting what is necessary to properly understand your conclusions on substantive questions of in terest to the primary audience. It is less important to worry about the latter two items in the Appendix which is expected to be more detailed and process-oriented. However, there should be en ough text annotating the technical material in the Appendix so that the reader can see how and why you carri ed out the more detailed work shown there. The data analysis report isn’t quite like a research paper or term paper in a class, nor like a research article in a journal. It is meant, primarily, to start an organized co nversation between you and your client/collaborator. In that sense it is a kind of “internal” communication, sort o f like an extended memo. On the other hand it also has an “external” life, informing a boss or supervisor w hat you’ve been doing. 2 Now let’s consider the basic outline of the data analysis report in more detail: 1. Introduction. Good features for the Introduction include: Summary of the study and data, as well as any relevant substan tive context, background, or framing issues. The “big questions” answered by your data analyses, and summ aries of your conclusions about these questions. Brief outline of remainder of paper. The above is a pretty good order to present this material in as well. 2. Body. The body can be organized in several ways. Here are two that of ten work well: Traditional. Divide the body up into several sections at the same level as t he Introduction, with names like: – Data – Methods – Analysis – Results This format is very familiar to those who have written psych r esearch papers. It often works well for a data analysis paper as well, though one problem wit h it is that the Methods section often sounds like a bit of a stretch: In a psych research paper the Methods section describes what you did to get your data. In a data analysis paper, you sho uld describe the analyses that you performed. Without the results as well, this can be prett y sterile sounding, so I often merge these “methods” pieces into the “Analysis” section when I wr ite. Question-oriented. In this format there is a single Body section, usually called “Analysis”, and then there is a subsection for each question raised in the introduction, usually taken in the same order as in the introduction (general to speci c, decre asing order of importance, etc.). Within each subsection, statistical method, analyses, and conclusion would be described (for each question). For example: 2. Analysis 2.1 Success Rate Methods Analysis Conclusions 2.2 Time to Relapse Methods Analysis Conclusions 3 2.3 E ect of Gender Methods Analysis Conclusions 2.4 Hospital E ects Methods Analysis Conclusions Etc. . . Other organizational formats are possible too. Whatever th e format, it is useful to provide one or two well-chosen tables or graphs per question in the body of the report, for two reasons: First, graphical and tabular displays can convey your points more e ciently than words; and second, your “skimming” audiences will be more likely to have their eye caught by an in teresting graph or table than by running text. However, too much graphical /tabular material will break up the ow of the text and become distracting; so extras should be moved to the Appendix. 3. Conclusion(s) /Discussion. The conclusion should reprise the questions and conclusion s of the in- troduction, perhaps augmented by some additional observat ions or details gleaned from the analysis section. New questions, future work, etc., can also be raise d here. 4. Appendix /Appendices. One or more appendices are the place to out details and ancill ary materials. These might include such items as Technical descriptions of (unusual) statistical procedur es Detailed tables or computer output Figures that were not central to the arguments presented in t he body of the report Computer code used to obtain results. In all cases, and especially in the case of computer code, it i s a good idea to add some text sentences as comments or annotations, to make it easier for the uniniti ated reader to follow what you are doing. It is often di cult to nd the right balance between what to put in the append ix and what to put in the body of the paper. Generally you should put just enough in the body to make the point, and refer the reader to speci c sections or page numbers in the appendi x for additional graphs, tables and other details. 4
BUSINESS DATA ANALYTICS Assignment: Jamie received 105 responses, which are given in the Excel file Drout Advertising Survey. Review the questionnaire and classify the data collected from each que
Question Variab le 1 Gender 2 Age 3 Ed u cat io n 4 Income 5 Sp en d in g 6 Ad Frequency 7 St ereo t yp e 8 Reinforcing 9 Transform 10 Em p o w erm en t % Su rvey Q u est io n Wh at is yo u r g en d er? Male Female Wh at is yo u r ag e? Wh at is t h e h ig h est level o f ed u cat io n yo u h ave co m p let ed ? Some High Sc hool Clas s es High School Diploma Some Under gr aduate Cour s es As s oc iate Degr ee Bac helor Degr ee Mas ter Degree J.D. M.D. Doctorate Degree Wh at is yo u r an n u al in co m e? $0 to < $10,000 $10,000 to < $20,000 $20,000 to < $30,000 $30,000 to < $40,000 $40,000 to < $50,000 $50,000 to < $60,000 $60,000 to < $70,000 $70,000 to < $80,000 $80,000 to < $90,000 $90,000 to < $110,000 $110,000 to < $130,000 $130,000 to < $150,000 $150,000 or More On average, how much do you pay for beauty and hygiene products or services per year? Include references to the following products: soap, deodorant, shampoo, conditioner, lotion, perfume, cologne, make-up, chemical hair color, razors, skin care, feminine care, and salon services. On average, how many beauty and hygiene advertisements, if at all, do you think you view or hear per day? Include references to the following advertisements: television, billboard, internet, rad io , n ew sp ap er, mag az in e, an d d irect mail. On average, how many of those advertisements, if at all, specifically subscribe to gender roles and stereotypes? On the following scale, what role, if any, do these advertisements have in reinforcing specific gender stereotypes? Drastic Influential Limited Trivial None To what extent do you agree that empowerment advertising, which explicitly communicates the unique differences in each individual, would help transform cultural gender stereotypes? Str ongly Agr ee Agr ee Somewhat Agr ee Neutral Somewhat Dis agr ee Disagree Str ongly Dis agr ee On average, what percentage of advertisements that you view or hear per day currently utiliz e empow erment advertising? Re s ponde nt Gender Age Education Income Spending 1 Fe ma le 23 Some undergraduate courses $10,000 to < $20,000 $500.00 2 Ma le 22 High school diploma $20,000 to < $30,000 $75.00 3 Fe ma le 24 Bachelor Degree $60,000 to < $70,000 $1,500.00 4 Fe ma le 23 Bachelor Degree $30,000 to < $40,000 $500.00 5 Fe ma le 23 Bachelor Degree $30,000 to < $40,000 $4,000.00 6 Fe ma le 24 Bachelor Degree $10,000 to < $20,000 $300.00 7 Fe ma le 30 Doctorate Degree $60,000 to < $70,000 $700.00 8 Fe ma le 28 Bachelor Degree $50,000 to < $60,000 $500.00 9 Fe ma le 20 Some undergraduate courses $0 to < $10,000 $1,000.00 10 Ma le 24 Some undergraduate courses $20,000 to < $30,000 $337.00 11 Fe ma le 24 Associate Degree $20,000 to < $30,000 $600.00 12 Fe ma le 24 Bachelor Degree $30,000 to < $40,000 $240.00 13 Fe ma le 27 Bachelor Degree $70,000 to < $80,000 $3,000.00 14 Fe ma le 24 Master Degree $0 to < $10,000 $250.00 15 Fe ma le 21 Bachelor Degree $0 to < $10,000 $500.00 16 Fe ma le 23 Master Degree $70,000 to < $80,000 $2,500.00 17 Fe ma le 23 Master Degree $50,000 to < $60,000 $2,000.00 18 Fe ma le 20 Some undergraduate courses $0 to < $10,000 $400.00 19 Fe ma le 46 J.D. $10,000 to < $20,000 $100.00 20 Fe ma le 23 Bachelor Degree $40,000 to < $50,000 $1,000.00 21 Fe ma le 23 Some undergraduate courses $10,000 to < $20,000 $750.00 22 Ma le 23 Associate Degree $10,000 to < $20,000 $400.00 23 Fe ma le 21 Some undergraduate courses $0 to < $10,000 $800.00 24 Ma le 23 Associate Degree $20,000 to < $30,000 $500.00 25 Ma le 19 Some undergraduate courses $0 to < $10,000 $600.00 26 Fe ma le 59 Associate Degree $150,000 or more $2,500.00 27 Fe ma le 65 Doctorate Degree $70,000 to < $80,000 $350.00 28 Ma le 32 Bachelor Degree $90,000 to < $110,000 $400.00 29 Fe ma le 50 Doctorate Degree $40,000 to < $50,000 $350.00 30 Ma le 23 Bachelor Degree $20,000 to < $30,000 $200.00 31 Fe ma le 31 Some undergraduate courses $20,000 to < $30,000 $200.00 32 Ma le 25 Bachelor Degree $0 to < $10,000 $100.00 33 Ma le 23 Some undergraduate courses $20,000 to < $30,000 $100.00 34 Fe ma le 55 J.D. $110,000 to < $130,000 $1,000.00 35 Fe ma le 68 Doctorate Degree $110,000 to < $130,000 $1,500.00 36 Fe ma le 21 Some undergraduate courses $0 to < $10,000 $50.00 37 Ma le 22 Bachelor Degree $20,000 to < $30,000 $100.00 38 Ma le 27 Master Degree $0 to < $10,000 $250.00 39 Fe ma le 33 Doctorate Degree $60,000 to < $70,000 $250.00 40 Fe ma le 32 Master Degree $70,000 to < $80,000 $310.00 41 Fe ma le 22 Some undergraduate courses $0 to < $10,000 $40.00 42 Fe ma le 44 Bachelor Degree $60,000 to < $70,000 $1,000.00 43 Fe ma le 49 Bachelor Degree $50,000 to < $60,000 $600.00 44 Fe ma le 22 High school diploma $10,000 to < $20,000 $5,000.00 45 Fe ma le 26 Master Degree $30,000 to < $40,000 $2,500.00 46 Fe ma le 49 Bachelor Degree $50,000 to < $60,000 $500.00 47 Fe ma le 58 Doctorate Degree $90,000 to < $110,000 $500.00 48 Fe ma le 61 Bachelor Degree $30,000 to < $40,000 $300.00 49 Fe ma le 21 Bachelor Degree $0 to < $10,000 $1,200.00 50 Fe ma le 24 Bachelor Degree $10,000 to < $20,000 $400.00 51 Fe ma le 27 Bachelor Degree $40,000 to < $50,000 $500.00 52 Fe ma le 21 Some undergraduate courses $0 to < $10,000 $400.00 53 Fe ma le 25 Associate Degree $0 to < $10,000 $50.00 54 Fe ma le 23 Bachelor Degree $20,000 to < $30,000 $500.00 55 Fe ma le 23 Bachelor Degree $50,000 to < $60,000 $1,500.00 56 Fe ma le 23 Bachelor Degree $20,000 to < $30,000 $150.00 57 Fe ma le 23 Bachelor Degree $10,000 to < $20,000 $400.00 58 Ma le 23 Bachelor Degree $0 to < $10,000 $75.00 59 Fe ma le 46 Some undergraduate courses $0 to < $10,000 $600.00 60 Fe ma le 39 Doctorate Degree $60,000 to < $70,000 $100.00 61 Ma le 27 Bachelor Degree $20,000 to < $30,000 $390.00 62 Fe ma le 24 Bachelor Degree $30,000 to < $40,000 $350.00 63 Ma le 23 Bachelor Degree $0 to < $10,000 $200.00 64 Ma le 22 Bachelor Degree $0 to < $10,000 $25.00 65 Fe ma le 24 Bachelor Degree $0 to < $10,000 $300.00 66 Fe ma le 20 Some undergraduate courses $0 to < $10,000 $800.00 67 Fe ma le 23 Bachelor Degree $10,000 to < $20,000 $300.00 68 Ma le 25 Bachelor Degree $20,000 to < $30,000 $100.00 69 Ma le 19 Some undergraduate courses $10,000 to < $20,000 $250.00 70 Fe ma le 25 Master Degree $10,000 to < $20,000 $180.00 71 Fe ma le 23 Bachelor Degree $10,000 to < $20,000 $500.00 72 Fe ma le 23 Some undergraduate courses $10,000 to < $20,000 $400.00 73 Fe ma le 20 Some undergraduate courses $0 to < $10,000 $250.00 74 Fe ma le 64 Doctorate Degree $90,000 to < $110,000 $500.00 75 Fe ma le 49 Master Degree $30,000 to < $40,000 $20.00 76 Fe ma le 26 Bachelor Degree $0 to < $10,000 $240.00 77 Fe ma le 29 Some undergraduate courses $10,000 to < $20,000 $600.00 78 Fe ma le 23 Master Degree $30,000 to < $40,000 $500.00 79 Fe ma le 23 Bachelor Degree $30,000 to < $40,000 $500.00 80 Fe ma le 22 Some undergraduate courses $30,000 to < $40,000 $1,500.00 81 Fe ma le 26 Master Degree $20,000 to < $30,000 $200.00 82 Fe ma le 24 Bachelor Degree $10,000 to < $20,000 $1,000.00 83 Fe ma le 29 Master Degree $30,000 to < $40,000 $1,500.00 84 Ma le 27 High school diploma $20,000 to < $30,000 $50.00 85 Fe ma le 22 Bachelor Degree $10,000 to < $20,000 $300.00 86 Fe ma le 54 Doctorate Degree $90,000 to < $110,000 $2,000.00 87 Fe ma le 26 Master Degree $10,000 to < $20,000 $550.00 88 Fe ma le 40 Some undergraduate courses $90,000 to < $110,000 $1,000.00 89 Fe ma le 19 Some undergraduate courses $0 to < $10,000 $80.00 90 Fe ma le 24 Bachelor Degree $50,000 to < $60,000 $1,500.00 91 Fe ma le 22 Bachelor Degree $10,000 to < $20,000 $200.00 92 Fe ma le 24 Bachelor Degree $20,000 to < $30,000 $250.00 93 Fe ma le 20 Some undergraduate courses $0 to < $10,000 $200.00 94 Fe ma le 24 Associate Degree $30,000 to < $40,000 $100.00 95 Fe ma le 27 Bachelor Degree $30,000 to < $40,000 $1,500.00 96 Fe ma le 30 Some undergraduate courses $50,000 to < $60,000 $600.00 97 Fe ma le 25 Master Degree $10,000 to < $20,000 $50.00 98 Fe ma le 54 Master Degree $50,000 to < $60,000 $100.00 99 Ma le 37 Bachelor Degree $110,000 to < $130,000 $400.00 100 Fe ma le 23 Master Degree $80,000 to < $90,000 $200.00 101 Fe ma le 21 Some undergraduate courses $0 to < $10,000 $200.00 102 Fe ma le 42 Doctorate Degree $50,000 to < $60,000 $600.00 103 Fe ma le 23 Bachelor Degree $10,000 to < $20,000 $380.00 104 Fe ma le 32 Master Degree $10,000 to < $20,000 $100.00 105 Fe ma le 24 Bachelor Degree $30,000 to < $40,000 $250.00 Ad Fre que nc y Stereotype Re inforc ing Tra ns form Empowerment% 10 9 Drastic Strongly Agree 10% 15 14 Influential Somewhat Agree 2% 10 10 Influential Ne u tra l 8% 10 10 Influential Agree 0% 75 75 Influential Agree 10% 5 5 Drastic Agree 10% 6 6 Influential Somewhat Agree 10% 10 6 Influential Somewhat Agree 5% 15 13 Drastic Strongly Agree 10% 40 38 Drastic Strongly Agree 1% 37 35 Influential Strongly Agree 3% 15 15 Limited Agree 0% 2 2 Influential Somewhat Agree 0% 20 18 Influential Ne u tra l 10% 20 20 Influential Agree 10% 600 590 Drastic Strongly Agree 2% 50 48 Drastic Strongly Agree 1% 400 375 Influential Strongly Agree 5% 5 5 Influential Somewhat Disagree 0% 20 15 Influential Agree 10% 100 100 Drastic Strongly Agree 15% 3 2 Influential Agree 10% 10 10 Influential Strongly Agree 5% 50 10 Trivial Somewhat Agree 10% 15 14 Influential Agree 5% 20 20 Drastic Strongly Agree 0% 20 20 Influential Somewhat Agree 0% 5 5 Limited Somewhat Agree 0% 10 10 Drastic Strongly Agree 1% 150 135 Influential Somewhat Agree 0% 25 25 Drastic Ne u tra l 0% 5 5 Influential Somewhat Agree 0% 300 300 Drastic Agree 1% 50 40 Influential Agree 10% 150 150 Influential Agree 0% 100 100 Drastic Agree 0% 3 1 Limited Strongly Agree 2% 5 4 Influential Somewhat Agree 20% 6 6 Drastic Somewhat Agree 0% 12 12 Influential Agree 0% 2 2 Drastic Strongly Agree 0% 3 3 Drastic Agree 10% 10 8 Influential Somewhat Agree 0% 5 5 Drastic Strongly Agree 0% 10 10 Limited Agree 5% 10 8 Influential Agree 0% 20 20 Influential Somewhat Agree 5% 50 50 Drastic Somewhat Agree 10% 10 10 Influential Agree 0% 20 20 Drastic Somewhat Agree 0% 20 17 Influential Somewhat Agree 15% 25 25 Influential Strongly Agree 0% 20 20 Drastic Strongly Agree 0% 4 2 Influential Agree 20% 25 25 Drastic Somewhat Agree 10% 10 8 Influential Strongly Agree 10% 10 10 Influential Somewhat Agree 2% 10 8 Limited Agree 20% 150 150 Influential Strongly Agree 1% 15 10 Influential Somewhat Agree 1% 50 45 Drastic Strongly Agree 1% 20 20 Influential Agree 10% 5 5 Influential Somewhat Agree 5% 5 2 Trivial Disagree 0% 50 50 Influential Somewhat Agree 0% 10 10 Drastic Strongly Agree 10% 15 15 Drastic Strongly Agree 10% 4 3 Influential Somewhat Agree 25% 2 1 Influential Agree 10% 5 5 Drastic Agree 0% 20 20 Drastic Somewhat Agree 5% 25 25 Influential Strongly Agree 1% 30 30 Drastic Agree 2% 55 55 Influential Ne u tra l 0% 0 0 Influential Strongly Agree 0% 5 3 Influential Agree 10% 20 19 Drastic Strongly Agree 5% 35 34 Influential Strongly Agree 10% 9 9 Drastic Strongly Agree 7% 2 2 Drastic Strongly Agree 0% 45 42 Drastic Somewhat Agree 10% 50 50 Influential Strongly Agree 10% 10 10 Influential Ne u tra l 10% 7 7 Influential Somewhat Agree 8% 10 7 Influential Somewhat Agree 10% 10 9 Influential Agree 1% 20 20 Influential Somewhat Agree 0% 20 20 Influential Agree 0% 35 35 Influential Agree 5% 6 6 Influential Agree 0% 10 8 Influential Somewhat Agree 20% 50 50 Drastic Somewhat Agree 0% 65 65 Drastic Strongly Agree 5% 1100 1050 Influential Strongly Agree 5% 3 3 Influential Somewhat Agree 0% 5 5 Drastic Strongly Agree 10% 1 1 Influential Somewhat Agree 10% 10 10 Influential Agree 0% 65 65 Trivial Ne u tra l 30% 3 2 Influential Somewhat Agree 15% 2 2 Influential Somewhat Agree 1% 3 3 Influential Somewhat Agree 0% 35 35 Drastic Strongly Agree 5% 2 2 Drastic Somewhat Agree 0% 6 6 Influential Agree 2%

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