Regression and Correlation Asthma is one of the most common chronic disorders in childhood, currently affecting an estimated 7.1 million children...

Regression and Correlation

Asthma is one of the most common chronic disorders in childhood, currently affecting an

estimated 7.1 million children under 18 years. During the period 2008-2010, asthma prevalence

was higher among those with family income below the poverty level. Use an Excel spreadsheet

to examine the association between poverty and child asthma in 31 states with information on

child asthma in 2012. State poverty levels come from the 2010-2012 American Community

Survey, and current child asthma prevalence rates come from the Behavioral Risk Factor

Surveillance System (BRFSS).

a. Identify the independent variable.

b. Identify the dependent variable.

c. Calculate the least squares lines. Put the equation in the form of y = a + bx

d. Interpret the regression coefficient for this example.

e. Interpret the Y-intercept for this example.

f. Find the correlation coefficient and write down a statement describing the association

between poverty rates and male asthma prevalence rates in these 31 states.

g. Use the regression equation to predict male asthma prevalence rates for Arkansas, New

Hampshire, and Mississippi (poverty rates are in the Excel file).

h. Is the correlation coefficient between poverty rates and male asthma prevalence rates

statistically significant? Specify the null and research hypotheses, significance level, and

criterion you used to reach your conclusion.

BONUS POINTS: Make a scatter plot of the data. Remember to include a title for your graph

and label the X-axis and Y-axis.

Data Sheet link here:

https://blackboard.ualr.edu/bbcswebdav/pid-2016882-dt-content-rid-32972091_1/xid-32972091_1