Pick one of the four articles below and respond to the following prompts: - Which article did you choose? - What are the researchers looking to test? - What is an independent and dependent variable pair in this study? (Researchers usually have many - you can focus on just one!) - What's the correlation coefficient between these two variables?

Table 1. County-Specific Autism Prevalence and Mean Precipitation Using Ordinary Least Squares Regression Variable

Coefficient (95% Confidence Interval)

Mean annual precipitation in inches, 1987-2001

0.0034 (0.0018 to 0.0050)a Logarithm of county population 0.026 (0.001 to 0.051)b County per capita income, $ 0.0039 (0.0079 to 0.0002) Ethnicity, % of 6- to 18-year-olds in the county Hispanic 0.00043 (0.0023 to 0.0014) Black 0.00017 (0.0050 to 0.0053) American Indian or Alaska native 0.0080 (0.013 to 0.0032)a Indicator of whether a county is located in Oregon

0.461 (0.37 to 0.55)a

Indicator of whether a county is located in Washington

0.042 (0.0069 to 0.092)

Indicator of whether a California county has a regional center

0.030 (0.016 to 0.076) Constant 0.0080 (0.245 to 0.229) No. of observations 119 R2 0.77

- There's a lot of potential lurking variables with this article (urbanicity) - Read the introduction on the first page (spills over to the second page) - The researchers have several different models, but you can focus on just one. Check out page 3 of the PDF where it has a heading "Table 1". Read that paragraph, then scroll to page 6 of the PDF to see the table results. Precipitation is the "x" variable (independent variable) and percent cases of autism is the "y" variable (dependent variable) - The slope of the regression equation is in the right column. The R^2 at the bottom tells you how correlated the variable is!