Quantitative Data Analysis

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Presentation transcript:

Quantitative Data Analysis Leonardo Veliz, Ph.D

Analysing quantitative data Overview of descriptive statistics - Measures of central tendency - Measures of variability Overview of inferential statistics - choosing a test to test hypotheses - parametric vs. non-parametric tests Identifying a relationship & comparing means

Measures of central tendency Mean : the average of a distribution (we add all values and divide by number of observations) Median: The mid-point in a distribution of values Mode: The value that occurs most frequently in a distribution Note: sometimes quantitative researchers prefer to disregard some extreme values rather than use the median or mode.

Measures of variability Range: distance between the highest and the lowest value Standard Deviation: the average amount of deviation from the mean Variance: the standard deviation squared Where data are not normally distributed (e.g. income and wealth), measures of dispersion are very useful (quartiles, deciles, percentiles)

Small task1 Please use the hypothetical data in your handouts to Calculate the mean, median and mode: which ones best represents your data? Calculate the range of the values, the variance and the standard deviation

Some tests for comparing averages Independent T-test: comparing 2 groups (male vs. female) Paired sample T-test: one group on 2 occasions (BAES cohort tested in Sept and then in June) ANOVA: When the independent variable has more than 2 levels (teachers with 1-5, 6-10, 11-15, 16+ years of experience) MANOVA: when we have more than 1 dependent variables (We are interested in the interaction (the multivariate effect)

Introducing SPSS Very powerful tool for analysing quantitative data Looks like Excel (rows as cases & columns as variables) Data view window: where you enter your data Variable view window: where you define your variables Output window: it reports the results of your analysis (PGCE survey example)

Quantitative data analysis references Diamond, I. (2001). Beginning statistics. London: Sage. Hinton, P (1995) Statistics explained. London: Routledge Salkind, N. (2008) Statistics for people who (think they) hate statistics. London: Sage. Tabachnick, B. & Fidell, L. (2001). Using multivariate statistics. Boston, MA: Allyn & Bacon.

Quantitative data analysis using SPSS Colman. A (2008). A crash course in SPSS for windows 14, 15 and 16. Chichester: Willey. Field, A. (2005) Discovering statistics using SPSS. London: Sage. Kinnear, P. & Gray, C. (2009). SPSS 16 made simple. Hove: Psychology Press. Miller, R. et al (2002). SPSS for Social Scientists. Bristol: Palgrave. Pallant, J (2007) SPSS survival manual. Maidenhead: OUP