Hashimoto et al. (A-7) developed a multiple regression model to predict the number of visits to emergency rooms at Jikei University hospitals in Tokyo for children having an asthma attack. The researchers found that the number of visits per night increased significantly when climate conditions showed a rapid decrease from higher barometric pressure, from higher air temperature, and from higher humidity, as well as lower wind speed. The final model demonstrated that 22 percent of the variation in the number of visits was explained by variation in the predictor variables mentioned above with eight other significant climate variables.

(a) Which is more relevant, regression analysis or correlation analysis, or are both techniques equally relevant?

(b) Which is the dependent variable?

(c) What are the independent variables?

(d) What are the appropriate null and alternative hypotheses?

(e) Which null hypotheses do you think were rejected? Why?

(f) Which is the more relevant objective, prediction or estimation, or are the two equally relevant? Explain your answer.

(g) What is the sampled population?

(h) What is the target population?

(i) Which variables are related to which other variables? Are the relationships direct or inverse?

(j) Write out the regression equation using appropriate numbers for parameter estimates.

(k) What is the numerical value of the coefficient of multiple determination?

(l) Give numerical values for any correlation coefficients that you can.