AboutJason Eisele Expertise I am qualified to answer probability questions through the undergraduate level. I can also assist with the first actuarial exam in probability and explain the roles of probability in applications such as economics and game theory.
I hope to address any topics that I am currently unfamiliar with during my studies as an actuary.
Experience I am beginning employment as an Actuarial Assistant with a major auto insurer. On the side, I have experience applying probability to poker at a highly competitive level.
Organizations Mensa
Education/Credentials University of Rochester Class of 2008:
Bachelor of Arts, Mathematics and Economics
Certificate in Actuarial Studies
Certificate in Mathematical Modeling in Political Science and Economics
Certificate in Management Studies with track in Accounting and Finance
Question I don't know where to start with my project. I have to compare two variables. area of interest/why the data are of interest to me? population? variable? data source? data (a set of at least 12 pairs of data values for a numeric variable? Construct a scatter plot(label x and y axis? 9. negative, positive or no correlation? calculate the correlation coefficient r and verify you conclusion in 9? Find equation of the regression line, add the line to your scatter plot, does the line appear to be a good fit? Use the equation of the regression line to make 2 predictions.
Answer Hi Tonya,
Is this a final project for a course? This is testing a lot of information, so I recommend reviewing a textbook and/or the links below:
When deciding on your variables, try to think of two quantitative statistics that may have something to do with one another. A very basic example is height and weight of people or animals. You can also see how one variable changes over time (box office receipts at movie theaters) or how two variables correlate due to a third variable (ice cream consumption and violent crime with respect to time).
My last example shows that correlation of two variables does NOT imply causation. It has been shown that ice cream is consumed most during the summer (because of the climate) and that violent crime occurs most during the summer as well (because of fewer people at school or work, among other things). Because ice cream consumption and violent crime rates move together over time, they are positively correlated. This does NOT, however, mean that ice cream consumption causes crime or vice versa.
The case of correlation without causation is one of the most important lessons from basic statistics, so my recommendation to you is to look for two correlated variables that have no causal effect on one another.
