Requirements (Part 2)
                  
     1.Data Analysis and Interpretation
     2.Techniques of data analysis
     3.Task Description 
     4.Task Analysis 
          Data Analysis and Interpretation
  The kind of analysis that can be performed on a set of data will be influenced by : 
   1.goals identified at the outset 
   2.data actually gathered. 
  Broadly speaking, you may take 
   ·
    a qualitative analysis approach 
   ·
    a quantitative analysis approach 
  In a combination of qualitative and quantitative. 
  The last of these is very common as it provides a more comprehensive account of 
  the behaviour being observed or performance being measured. 
  Most analysis, whether it is quantitative or qualitative, begins with initial reactions 
  or observations from the data.
   Interpretation of the findings often proceeds in parallel with analysis, but there are 
  different ways to interpret results and it is important to make sure that the data 
  supports your conclusions. 
  Techniques of data analysis:
 1)  Quantitative data  : is data that is in the form of numbers, or that can easily be 
  translated into numbers. 
  For example, the number of years’ experience the interviewees have, the number 
  of projects a department handles at a time, or the number of minutes it takes to 
  perform a task. 
  2) Qualitative data: is not expressed in numerical terms. 
  For  example,  qualitative  data  includes  descriptions,  quotes  from  interviewees, 
  vignettes of activity, and images. 
  Simple Quantitative Analysis. 
  Averages and percentages are fairly well-known numerical measures. However, there 
  are three different types of average and which one you use changes the meaning of 
  your results. These three are: mean, median, and mode. 
  Mean  : refers to the commonly understood interpretation of average. 
  Median : is the middle value of the data when the numbers are ranked. 
  Mode : is the most commonly occurring number. 
  Median and mode are less well-known but are very useful. 
  For example : in a set of data (2, 3, 4, 6, 6, 7, 7, 7, 8), 
  the median is 6 
  the mode is 7, 
  the mean is 50/9 = 5.56. 
  In this case, the difference between the different averages is not that great. 
  However, consider the set (2, 2, 2, 2, 450). Now the median is 2, the mode is 2, and 
  the mean is 458/5 = 91.6! 
  Simple Qualitative Analysis. 
  There are three simple types of qualitative analysis, which include: 
  1- Identifying recurring patterns and themes 
  2 - Categorizing data 
  3- Analysing critical incidents. 
  These are not mutually exclusive and can be used in combination. 
  Tools to Support Data Analysis.  
  Two well-known tools that support some of these data analysis activities are Nvivo 
  and Atlas.ti. 
  SPSS (Statistical Package for the Social Sciences)  
  Is one of the more popular quantitative analysis packages that supports the use of 
  statistical tests. 
   It  is  a  sophisticated package offering a wide range of statistical tests such as 
   frequency distributions, rank correlations (to determine statistical significance), 
   regression analysis, and cluster analysis. SPSS assumes that the user knows and 
   understands statistical analysis.