Analysing-quantitative-data.ppt
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1、Analysing dataQualitative v quantitative dataQualitative data*uses open ended questions to get in depth answers*avoids closed yes/no questions*idea is that people should share their thoughtsQuantitative data*gather numerical information*sample sizes larger*usually questionnaire research where result
2、s can be summarised numbers percentages averages*involves yes/no,Likert scale,etcBasic comments on data*choose the easiest way to analyse your data*keep it simple*choose the data presentation method that best communicates the information1.Preparing the data for analysis *Data types *data can be put
3、into categories e.g.hatchback cars saloon cars estate cars BUT make sure the categories do not overlap *data can be quantifiable e.g.you give a position on an attitude scale a number*Data collection*if you issue a questionnaire on line and it is returned on line analysis of data can be easierBUT man
4、y questionnaires are returned manually,so:-*you have to prepare data *you have to code data*Coding data*with numbers,use the numbers when coding e.g.employee salary 32,000 code it 32,000 analyse by group 30-40,000*with data from open ended questions,coding can be done after you have collected the da
5、ta as you will be unsure of the likely responses.Thus:-*wait for 20-30 responses *look at responses and develop broad groupings *divide the broad groupings into sub groups *allocate codes *code further responses e.g.What are the key factors that might improve your degree?Answers less hours more free
6、 time more lectures more books fewer assignments better lecturersCould categorise these as Academic Non-academicOR Factors that can be changed quickly Factors that can not be changed quickly 2.Presenting your dataYou need to remember what your research objectives areBUT your data may also show resul
7、ts you had not anticipatedWhat do you look for to get started?How do you present your data?Highest and lowest valuesshown as a bar chartStudent attendance at seminarsTrendsused for data collected over timecan be shown in a graphProportion of population in a categorycan be shown in a pie chart Studen
8、ts attending each seminarYou may also want to make comparisonsHighest and lowest comparisonsYou can use a bar chartStudent attendance per group each weekYou can also compare trendsStudent attendance by group each week3.Describing data using statistics How do you describe your data using statistics?H
9、ere you will be discussing such as:-A.Central tendency i.e.most common,middling or average value *mode:the value that occurs most frequently e.g.the most common(modal)colour for new cars last year was red*median the middle value of a distribution*mean or average BUT this might be skewed by a few ext
10、reme valuesExampleFamily Income()1 25,000 Mean 55,000(average)2 30,0003 30,0004 30,000 Mode 30,000(most5 30,000 frequent value)6 40,0007 40,0008 45,000 Median 35,000(middle 9 50,000 value)10 230,000Which calculation makes most sense?B.Dispersion around the central tendencyThis is the distribution of
11、 the data*a quick calculation is to look at the difference between the highest and lowestBUT this may not have much meaning*instead you can use quartiles *lower quartile-value below which a quarter of your data falls *upper quartile-value above which a quarter of your data falls*you may want to desc
12、ribe how data is spread around the mean.If the data values are all close to the mean,then the mean is more typical than if they vary widely.To describe the extent of spread of quantifiable data you can use the standard deviation 4.Looking at the relationships in the dataThe probability is of your te
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