Managing a Successful Business Project | My Assignment Tutor

11Session 8:Data AnalysisUnit 6: Managing a Successful Business ProjectTask 5: Analyse research and data using appropriate toolsand techniques.Dr Reza Aboutalebi2OutlinesAnalysing qualitative dataAnalysing quantitative dataEvaluating the chosen data analysistechniques23Analysing QualitativeDataQualitative Analysis TechniquesQualitative (Non-Statistical) analysis usually coversqualitative data /research.Interview is the most common Research Instrumentfor collecting Qualitative dataCommon qualitative (non-statistical) analysis are:Constant comparisonData codingContent analysisThematic analysis 43Qualitative Techniques: Constant ComparisonThe Constant Comparison method compare constantlythe collected data to each other and to data from otherresearch.Steps in constant comparison method:1. Writing done the interview (transcribing)2. Comparing the given answer to each question by differentinterviewees (participants),3. Finding the similarities of answers to each question (for examplein answering the first question, what similar issues mentioned byrespondents)4. Finding the differences of answers to each question (for examplein answering the first question, what different issues mentionedby respondents)5(Glaser & Strauss, 1985)Qualitative Techniques : Data CodingData Coding is “a systematic way in which to condenseextensive data sets into smaller analyzable units throughthe creation of categories and concepts derived from thedata.”“The process by which verbal data are converted intovariables and categories of variables using numbers(frequency), so that the data can be entered intocomputers for analysis.”For example in 8 interview about customer satisfaction:what are the similar variables & their frequency? Quality? (5times) Price? (7 times) Cost of service? (4 times)How these variables can be categorised? Financial? …6(Lockyer, 2004)(Bourque, 2004)4Qualitative Techniques: Content AnalysisContent Analysis is usually used when analyzingtext, documents or speech, and in seeing whatsignificant themes emerge from these social artefacts.7Qualitative Techniques: Thematic Analysis1- CodingDivide a text (interview transcript) into some small sections(2-3 lines) and give a code to each section2- Identifying ThemesPut some of the codes that are relevant, in same group3- Quantify codes and themesCalculate how many times each code or theme arementioned in one and all interviews4- Writing Analysis (report)Build a valid argument for choosing the themes. This isdone by reading the related literature. 8Thematic Analysis refers to any method of categorising segmentsof qualitative data into meaningful themes (Frith & Gleeson, 2004).Process of Thematic Analysis59Analysing QuantitativeDataDescriptive Statistics Mean (Average)MedianModeCentral Tendency Types of Descriptive StatisticsVarianceStandard DeviationRange Variation 10 Frequency The most common way to analyse numerical (quantitative)data is using statistical techniques. Statistical techniquescan be descriptive or analytical. Descriptive statisticsdescribe or summarize the data numerically.6FrequencyThe number of times that something happens within aparticular period of time or within a particular group of peopleFrequency can be shown by percentage.11How to change numbersto percentage:4+5+6+1+4 = 20 people4/20 = 0.2 = 20%5/20 = 0.25 = 25%6/20 = 0.3 = 30%1/20 = 0.05 = 5%Measures of Central Tendency Central TendencyMean(Average)MedianMode X nXni i== 1Midpoint ofranked valuesMostfrequentlyobservedvalue127MeanThe most common measure of central tendencyMean = sum of values divided by the number of valuesAffected by extreme values (outliers)0 1 2 3 4 5 6 7 8 9 10 Mean = 3 0 1 2 3 4 5 6 7 8 9 10 Mean = 4 351551 2 3 4 5= =+ + + +452051 2 3 4 10= =+ + + +13MedianIn an ordered array, the median is the “middle”number (50% above, 50% below)Not affected by extreme values0 1 2 3 4 5 6 7 8 9 10 Median = 3 0 1 2 3 4 5 6 7 8 9 10 Median = 3 148ModeA measure of central tendencyValue that occurs most oftenNot affected by extreme valuesUsed for either numerical or categorical (nominal –like gender, ethnicity, etc.) dataThere may be no modeThere may be several modes0 1 2 3 4 5 6 7 8 9 10 11 12 13 14Mode = 90 1 2 3 4 5 6No Mode15Review ExampleFive houses on a hill by the beach$2,000 K$500 K$300 K$100 K$100 KHouse Prices:£600,000500,000300,000200,000200,000– What is the mean?– What is the median?– What is the mode?16££££200,000£200,000£300,000£600,000£500,0009Review Example: Summary StatisticsMean: (£1,800,000/5)= £360,000Median: middle value of rankeddata= £300,000Mode: most frequent value= £200,000House Prices:£600,000500,000300,000200,000200,000Sum £1,800,00017When to use each measure?Mean is generally used, unless extreme values(outliers) exist.Median is used when there are outliers, since themedian is not sensitive to extreme values.Example: Median home prices may be reported for aregion – less sensitive to outliersMode is used when needing to know the value thatoccurs more often.Example: Country where more people saw a film,bought a product, etc.181019Evaluating DataAnalysis TechniquesAdvantages & disadvantages of Constant ComparisonAdvantagesIt shows what exactlysaid by participantsIt does not take toomuch timeIt can be done byalmost anyoneDisadvantagesFindings can berelatively basicIt may not be suitablefor large researchIt is limited toparticipants with thesame language2011Advantages and disadvantages of FrequencyAdvantagesEasy to use by theresearcherResults can beshown in form ofattractive graphsEasy to understandthe results byeveryone (managers)DisadvantagesIt does not showwhat factors affectthe resultsBeing frequent maynot mean beingimportantIt cannot explainwhy something ismore frequent21Advantages & disadvantages of Mean (average)AdvantagesIt describes theparticipants moreaccuratelyIt is an importantinformation to knowTakes every datavalue into accountDisadvantagesAn abnormally largeor small data canreduce its accuracyIt does not showwhat factors affectthe resultsIt does not showrelationship amongdata22


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