Mar Res Theo Chapt 14. Understanding quantitative data

Mar Res Theo Chapt 14. Understanding quantitative data

1. Planning the analysis

2. Understanding data

   • Concepts, questions and variables
     • Cases, variables and values
     • Data Entry
     • 4 Levels of Measurement important.. go to page 450
       • 1. Nominal scale numbers
       • 2. Ordinal scale numbers
       • 3. Interval scale numbers
       • 4. Ratio scale numbers
       • But why does all this matter?
       • Levels of measurement – Exam Q - - - identify 4 levels of measurement. And example of when used.
     • Editing and cleaning the dataset
       • Missing values
       • Inconsistencies, routeing errors and out of range values
       • Manipulation of variables

3. Types of data analysis

   • A note about inferential analysis

4. Univariate descriptive analysis

   • Frequency counts
     • Raw numbers, proportions, percentages and ratios
     • Graphical displays
       • Pie charts
       • Bar charts
       • Histograms
       • Line graphs
       • Choosing the scales for charts and graphs
   • Summary or descriptive statistics
     • Measures of central tendency
       • The mean
         • averagre?
       • The mode
       • The median
       • Properties of the mean, the mode and the median
     • Measures of variation
       • The range
       • The variance and the standard deviation
   • The story so far

5. Bivariate descriptive analysis

   • Ideas and hypotheses
   • The dependent and the independent variable
   • Cross-tabulations
     • How to read a cross-tabulation
     • Including 'don’t knows’ in calculating percentage figures
   • Compiling a set of cross-tabulations
   • Use of bases and filtering in tables
   • Labelling tables
   • Weighting the data

6. Data reduction

   • At the frequency count stage
   • At the univariate descriptive analysis stage
   • At the bivariate descriptive analysis stage
   • Data display as data reduction

7. Chapter summary

8. 4 main types of analysis =

   • univariate
     • bivariate
       • explanatory
         • inferential