1. Lecture 8 Distributions Percentiles and Boxplots Practical Psychology 1

7. The Boxplot Once these values have been calculated, this information can be used to draw a boxplot: Also known as a “ box-and-whisker ” plot Quick and easy method of checking distribution normality/ skewness. You need to know how to: draw boxplots by hand Produce them in SPSS and interpret them.

12. Boxplot and shape of distribution: normal distribution If data is normally distributed, the boxplot is symmetrical (i.e. the MEDIAN line is very close to the centre of the rectangle):

13. Boxplot and shape of distribution: positive skew Note MEDIAN Position: there is a greater proportion of data on the lower end of the scale

14. Note MEDIAN Position: there is a greater proportion of data on the upper end of the scale Boxplot and shape of distribution: negative skew

15. Boxplots in SPSS

16. Example: comparing male and female scores

17. Producing a Boxplot in SPSS SPSS menu  Graphs  Legacy Dialogs  Boxplot Simple Summaries of groups of cases Define

18. Drag the continuous variable to the “Variable box” and the categorical (e.g. gender) to the “Category Axis” box.

19. Each group is represented by a rectangle, in which 50% of the scores lie (this is the interquartile range, IQR) Y axis = scores (DV) The central line is the MEDIAN (Q2) X-axis: (IV) group: males vs. females

20. Some terminology H-spread = IQR (i.e., Q3-Q1) Upper Whisker = largest value Median (Q2) Lower Whisker = smallest value Lower Quartile (Q1) {lower Hinge} Upper Quartile (Q3) {upper Hinge}

21. Percentiles in SPSS

22. Analyze >Descriptive Statistics > Explore Put the IV (gender) in the factor list and the DV (scores) in the dependent list Menu on the right: Statistics > tick “Percentiles” “Continue”

23. Percentiles Output