Question

The owner of a chain of supermarkets notices that there was a positive correlation between the sales of beer and the sales of ice cream over the course of the previous year. During seasons when sales of beer were above average, sales of ice cream also tended to be above average. Likewise, during seasons when sales of beer were below average, sales of ice cream also tended to be below average. The owner is curious whether the observed association is due to a cause-and-effect relation between eating ice cream and desiring beer. To investigate this, the owner should use

A) The least-squares regression line.

B) The correlation coefficient.

C) The square of the correlation coefficient.

D) A well-designed experiment.

E) A 2-way table.

F) Extrapolation.

G) A residual plot.

H) A histogram.

I) A scatterplot.

J) A boxplot.

Answer 1

There is standard way to see if there is any relation between to variablres by using scatter plot. Its always helpfult to use this tecnique.

After that we may need to carry out correlation to see the strength of the relationship. A correlation coefficient near zero would suggest that the variables do not have a linear relationship with one another. A correlation coefficient near 1 or -1 would suggest that there is a strong linear relationship between the two variables.

Please note that this simple first step does not take into account the effect of additional confounding variables. For example, for the sales of beer and ice cream there is a season variable that may have effect on the outcomes. This is the case where regression (multivariate) analysis comes handy.

To state the results clearly, the extra data taken by repeatative procedures could be utilise. In our case data for sales on beer and ice cream for some years could be analysed by using proper experimental design.