STAT151 Chapter Notes - Chapter 6: Scatter Plot, Dependent And Independent Variables, Confounding

• School: University of Alberta
• Department: Statistics
• Course: STAT151
• Professor: Rosana Fok

Document Summary

Explains or causes change in the response variable. Observations are recorded in the form (x,y) Our sample of n bivariate observations is (x1, y1), (x2,y2), . , (xn,yn) Helps to evaluate the quality of the relationship and the ideal way to picture associations. Plot of pairs of observed values of 2 different quantitative variables between 2 quantitative variables. Example: the data in the following table gives the median income for full time workers ages 25 and older and how many years of schooling completed. x = years of schooling y = salary (dollars) *if you want to make a scatter plot with more than 1 group, then use different symbols for each group. *axes do not need to intersect at (0,0) Describe by the form, direction and strength of the relationship: direction (positive & negative association, form of relationship. Cluster (form a visible group within the plot: strength of the relationship. Strong (plots are not far from the linear line)