Data Analysis
Using Nonparametric Tests
A parameter is a population score, whereas a statistic is a score for a sample randomly drawn from the population. Parametric statistics make certian assumptions about population parameters.
- One assumption is that the scores in the population are normally distrubuted about the mean.
- Second, is that the population variances of the comparison groups in one'es study are approximately equal
When large deviations from these assumptions are present in the research data, parametric statistics should not be used and instead nonparametric statistics should be selected since they do not make assumptions about the shape or variance of population scores.Most continuous scores meet the criterion that scores being analysed are derived from a measure that has equal intervals. When scores are dichotomous or in the form of categories or ranks, one of the nonparametric statistics should be used for data analysis.Chi-square
It is a nonparametric statistical test that is used when research data are in the form of frequency counts. These frequency counts can be placed into two or more categories.
Should all forms of advertisement using women be banned?
Yes No
Male 34% 65%
Female 45% 55%
After forming the two categories, the number of persons who said 'yes' and 'no' or the frequencies are entered into each of the categories. The null hypothesis is that there is no significance difference between males and females with regards to their opinion on using women in advertisements. The percentages indicate clearly that more women agreed that it should be banned. The question is whether the difference between the groups is statistically signficant.
