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C hapter 16: Analysing survey data

C hapter 16: Analysing survey data . CONTENTS. Survey data analysis and types of research Spreadsheet analysis Statistical Package for the Social Sciences (SPSS) Preparation SPSS procedures The analysis process. Survey data analysis and types of research (Fig. 16.1).

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C hapter 16: Analysing survey data

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  1. Chapter 16: Analysing survey data

  2. CONTENTS • Survey data analysis and types of research • Spreadsheet analysis • Statistical Package for the Social Sciences (SPSS) • Preparation • SPSS procedures • The analysis process

  3. Survey data analysis and types of research (Fig. 16.1) A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  4. Explanatory research and causality • Necessary conditions: • Associationsbetween variables (A changes with B) • Time priority(B happens after A) • Non-spurious relationships (relationships ‘make sense’) • Rationale/theory (there should be an explanation) A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  5. Spreadsheet analysis (Fig. 16.1) • Example using data from Campus Sporting Life questionnaire (Fig. 10.21) • FREQUENCY procedure in Microsoft Excel used to produce: • frequency counts of coded variables • averages for numerical variables (age, spend) A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  6. Statistical Package for the Social Sciences (SPSS) • Software package produced by SPSS inc., owned by IBM • Analysis of questionnaire-based and other data • organised as cases with specified variables • SPSS is effective and one of the most popular packages. Its use in this book does not imply endorsement as ‘the best’ package. A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  7. SPSS procedures covered (Fig. 16.4) A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  8. Preparation: cases and variables: from Fig. 10.21 A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  9. Information required for each variable in the questionnaire • Name • Type – numeric, string (letters) or date • Width– max. no. of characters • Decimal places • Label – longer version of name • Values– for coded variables • Missing– blanks, no answer, etc. • Columns – no. of columns in Data View screen (see below) • Alignment – left, right, centre (in Data View) • Measure/data type – nominal, ordinal, scale A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  10. Variable names • Up to 8 characters (no spaces), beginning with a letter • Not allowed: ALL AND BY EQ GT LE LT NE NOT OR TO WITH • Can be: • Short version of item description (as used here), or • Var01, var02, var03 etc. or • Q1a, Q1b, Q2, Q3 etc A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  11. Types of measure • Nominal: described in words – eg. male/female • Ordinal: Ranked: 1, 2, 3 … means 1st, 2nd, 3rd …. • Scale: fully numeric A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  12. Variable View • Information on variables is entered in the SPSS ‘Variable View’ screen A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  13. Variable view screen (Fig. 16.8)

  14. Data View • Data entered directly on the Data View screen, or • Can be imported from a spreadsheet file A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  15. Data View screen (Fig. 16.9)

  16. Note to teachers • It is not envisaged that SPSS detailed procedures would be the subject of a PowerPoint presentation: students would benefit most from following the procedures in practical sessions • A copy of the Campus Sporting Life data files is available on the book website • However, teachers may wish to discuss the nature/ purpose of the various procedures. • Slides are therefore included with the outputs from the procedures A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  17. Descriptives: N, Minimum, Maximum, Mean & Standard Deviation for each variable. A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  18. Descriptives: output: first few variables (Fig. 16.11) A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  19. Frequencies • Simple counts/percentages of variables • Nominal/ordinal: straightforward • Numeric may need to be grouped – see Recode • Frequencies form the basis for a statistical summary/appendix – see Fig. 16.6 A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  20. Frequencies: output (Fig. 16.12) Frequencies for all variables: see Appendix 16.1 A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  21. Multiple Response • Two types of ‘Multiple Response’ • Dichotomy: Q. 2: use of services: 4 ‘yes/no’ variables • Best combined into one table • Category: Q. 6: Suggestions: up to three responses per respondent = 3 variables • Best combined into one table A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  22. Multiple Response output: Fig. 16.13 A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  23. Recode • Grouping/Re-grouping variable categories, especially: • presentational: numerical variables • theoretical eg. 5 categories of tourism or just two: leisure vs non-leisure? • Comparison – with other research • statistical reasons – see Ch. 17 • Examples: • uncoded, ‘spend’ has 9 different answers (see Appendix 16.1): recode into 4 groups • Student status has 2 F/T and 2 P/T categories: recode into F/T and P/T A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  24. Recode: output(Fig. 16.14) A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  25. Measures of central tendency: Mean, Median, Mode • Mean = average • Median = middle value when all cases ranked in order • Mode = most popular value • Only valid with scale and ordinal variables • Options: • Add to ‘Frequencies’ procedure • Use ‘Means’ A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  26. Mean, median, mode: ‘frequencies’ procedure (Fig. 16.15) A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  27. Means procedure (Fig. 16.15) Mean expenditure by student status A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  28. Crosstabulation • Table showing relationships between two or more variables • Table can include one or more of the following: • counts • row % • column % • total % • statistical tests – see Ch. 17 • Procedure: ‘Crosstabs’ A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  29. Crosstabs A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  30. Crosstabs contd: three variables A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  31. Weighting • Weighting discussed in Ch. 13 • ‘Weight cases’ procedure • eg. if Masters students under-sampled: • suppose masters students need to be given a weight of 1.3 • create new variable wt • for Masters students wt = 1.3; all others: wt = 1 • In ‘Weight cases’: weight by wt A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  32. Graphics • Types: • bar graph • stacked bar graph • pie chart • line graph • scatter plot • Different graph types suited to different data types A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  33. Data types and graphics (Fig. 16.18) * Grouped A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  34. Bar chart A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  35. Stacked bar chart A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  36. Pie chart A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  37. Line graph A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

  38. Scatterplot A. J. Veal & S. Darcy (2014) Research Methods for Sport Studies and Sport Management: A practical guide. London: Routledge

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