IntroductionYou are already familiar with data collection, tabulation, how to summarize data by measures of central tendency and measures of dispersion. Now you will learn how to evaluate the relationship between two variables.
As the temperature dips in winter, sales of woolen garments increase. Thus, the dip in temperature is related to sale of woolen garments. When school reopening time comes the sales of school books, bags and other stationery items begin to boom.
Now the questions that arise naturally in our minds are:
- Is there any association or connection between the two variables?
- If one variable changes in value, does it affect the other variable also?
- Do both the variables increase or decrease in the same direction?
- What is the strength of their relationship?
Francis Galton Karl Pearson Charles Spearman
Later Karl Pearson was instrumental in the development of this theory. One of his classic data sets (originally collected by Galton) involves the regression of sons' height upon that of their fathers'
Charles Spearman was also strongly influenced by the work of Francis Galton. In statistics, Spearman developed rank correlation, a non-parametric version of the conventional Pearson correlation.