ECON 2500 Lecture Notes - Dependent And Independent Variables, Scatter Plot, Confounding

• School: York University
• Department: Economics
• Course: ECON 2500
• Professor: all

Document Summary

Econ 2500 winter 2011 xianghong li. Chapter 2 looking at data relationships jan 18. The two variables are measured on the same individuals (or subjects). E. g. weight and height, gpa and mother"s education level. When there is a casual relationship: response variable: measures an outcome of a study, explanatory variable: explains or causes changes in the response variables. A scatterplot shows the relationships between two quantitative variables measured on the same individuals. There may be no explanatory-response distinction between the two variables. If there is a distinction, always plot the explanatory variable on the horizontal axis and response variable on the vertical axis. Overall pattern and striking deviations from that pattern. Describing the overall pattern by the form, direction and strength of the relationship: form, e. g. clusters, direction: positive vs. negative association. Correlation: measures the direction and strength of the linear relationship between two quantitative variables. No distinction between explanatory and response variables.