Quantitative analysis<\/strong> means the opposite, to measure by quantity rather than\nquality. When we do quantitative analysis, we are exploring facts, measures,\nnumbers, and percentages. When we do quantitative work, we work with numbers,\nstatistics, formulae, and data.<\/p>\n\n\n\n Both qualitative and quantitative analysis are vitally important\nto public relations.<\/p>\n\n\n\n EXAMPLES OF QUALITATIVE ANALYSIS<\/strong><\/p>\n\n\n\n Qualitative analysis focuses on why<\/strong>.\nWhy do people behave in certain ways? Why do they make decisions? Qualitative\nanalysis and research methods often include:<\/p>\n\n\n\n Qualitative analysis tends to look very deeply at a few things\nto understand the why.<\/p>\n\n\n\n EXAMPLES OF QUANTITATIVE ANALYSIS<\/strong><\/p>\n\n\n\n Quantitative analysis focuses\non what<\/strong>. What happened? How many people bought this product? What\npercentage of people considered this brand? Quantitative analysis and research\nmethods often include:<\/p>\n\n\n\n Quantitative analysis tends to look very broadly at many things\nto understand the what.<\/p>\n\n\n\n THE RIGHT METHOD FOR THE RIGHT\nPROBLEM<\/strong><\/p>\n\n\n\n Qualitative and quantitative analyses work best when blended together, a method appropriately called mixed method analysis.<\/p>\n\n\n\n We begin with qualitative research and analysis to understand\nthe problem broadly, to define what language we should be using.<\/p>\n\n\n\n Suppose we sell coffee. We might start a research process by\nasking people what they like about coffee in general.<\/p>\n\n\n\n Once we know what questions to ask, we switch to quantitative\nmethods to help us understand how many people have answers to our questions and\nwhat those answers are. Suppose, in our example, people said that the top\nreason for why they made the coffee choices they made was because of price.\nWe\u2019d run a survey asking people at what price they believe a good cup of coffee\nshould be.<\/p>\n\n\n\n Once we understand the numbers and math, we switch back to\nqualitative to ask why. Why did we receive the results we did in the\nquantitative research? Why did people make the choices they made? We would\nsurvey or interview a representative, random sample of our\nquantitatively-analyzed audience to understand why.<\/p>\n\n\n\n In our example, suppose we found out that a majority of people\nchose coffee priced at $1 or less. Why? What did the people who answered this\nhave in common \u2013 were they in similar professions? Perhaps they shared a common\ngender, geography, or ethnicity. We\u2019d then look at that group and return to\nqualitative research to ask more questions of them, about how coffee fits into\ntheir personal budgets.<\/p>\n\n\n\n We\u2019d then switch from qualitative to quantitative to gather more\ndata based on our refined understanding of our audience\u2026<\/p>\n\n\n\n \u2026 and the cycle repeats until we either have solid, defensible\nanswers to our questions or we run into resource constraints such as time and\nmoney.<\/p>\n\n\n\n Here\u2019s a helpful hint if you are ever stuck trying to remember the\nmeaning<\/p>\n\n\n\n of these words: quantitative and qualitative. After all, they are\nalmost <\/p>\n\n\n\n identical. Remember that qualitative has an \u201cl\u201d just like\n\u201cletters\u201d so that\u2019s <\/p>\n\n\n\n the one that deals with categorical data (non-numerical). GoodLuck!<\/p>\n\n\n\n![\"\"](\"http:\/\/thesis4u2000.com\/wp-content\/uploads\/2020\/01\/Picture4-1.png\")
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