Designing and Reporting Experiments in Psychology Peter Harris
     
 
 
 
Designing & Reporting Experiments in Psychology 3/e
 
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  A. Choosing a statistical test  
  B. Reporting specific inferential statistics  
  C. More on main effects, interactions and graphing interactions  
  D. Rules for writers  
  E. Reporting studies that include questionnaires  
  F. Experimental and nonexperimental data: Some things to watch out for  
  G. Some tips for advanced students to improve your experiments yet further  
  H. Some issues to consider in the RESULTS sections of your later reports and your projects  
  H1 The opening paragraph(s): setting the scene  
  H2 Reporting the descriptive and inferential statistics  
  H3 Including statistics of effect size and confidence intervals  
  H4 Further analyses on IVs with more than two levels  
  H5 Managing lengthy RESULTS sections  
  H6 An example RESULTS section for advanced students  
  I. Final year projects  
     
 
Related Statistics Books
 
  Pallant, SPSS Survival Manual  
     
  Greene & D'Oliveira, Learning to Use Statistical Tests in Psychology  
     
   
Results Section

 

H2 Reporting the descriptive and inferential statistics

The reporting of these is much as for the more basic experiments that you ran earlier in your career (see Sections 4.1 and 4.2 of the book). You may, however, have more than one set of data and associated analyses to report. If so, it may be necessary to construct separate tables of descriptive statistics for each set of data. Nevertheless, your goal should be to be concise: use as few tables of descriptive statistics as are necessary to report your data without confusing the reader.

If you have several DVs and associated analyses to report, consider the data and its attendant analyses as two sides of the same coin. So report them as a unit, by describing the data first and then the outcomes of the relevant inferential analyses before moving on to the next data/analysis set. Moreover, you should step through these in order of merit, starting with the data and analyses that are central to the experimental hypothesis and working through to the material that is illuminating but essentially ancillary. The principal task is to make clear precisely how the data were analysed, what the outcome of each particular analysis was (making it clear in the process to which each belongs) and, if you are testing for significance, whether the outcome was statistically significant and at what level.

 

 

 

 

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