A study revealed a strong, linear, negative association between a decrease in salary and amount spent on clothes. Another study
revealed a strong, linear, negative association between decrease in salary and amount spent on food. When the data were combined, the association became positive. What is this an example of? A. simpson's paradoxB.observational studyC.experimental studyD.cause-and effect realtionshipE.error by the statistician
The Simpson's paradox was named after Edward Simpson, the person who described this paradox for the first time in 1951. In this paradox, you find two contrary patterns. For example, a positive and a negative correlation, depending on how data is analyzed. The differences in the analyses are how data are grouped. This paradox is observed often in social researches. Most of the times, results are affected by the sample on each group or additional information related to the data.
Multiply top so y values cancel out, so multiple top by -3. Y values cancel out. You combine top and bottom equations, x=2. Plug 2 in first equation for x. Y=4
