What does this multiple regression of SO2 pollution in US cities as explained by

Question

What does this multiple regression of SO2 pollution in US cities as explained by four different predictors tells you?

Estimates in the table are the intercept and partial regression slopes for each predictor variable (Temp: Average Temperature; Man: Number of factories with >20 employees; Wind: Average wind velocity; Rain: Average precipitation). Question 9 options:

a) SO2 pollution was related positively to temperature, number of factories and Rain

b) SO2 pollution was related negatively to temperature, number of factories and Rain

c) SO2 pollution was related negatively to number of factories and positively to temperature and Rain d) SO2 pollution was related positively to number of factories and negatively to temperature and wind

SO2 pollution was related positively to number of factories and negatively to temperature and wind

d)

SO2 pollution was related positively to number of factories and negatively to temperature and wind

Jordan Pogorzelski s × x * Homework 5 Spring X/ D Homework Quiz 5.pc xe Chegg Study Guide C Dfile://C/Users/Jordan/Downloads/Homework%20Qu.2%205.pdf O STSnine-North Am Charts & Statistics- × predictor variaDie (iemp: Average iemperatur Average wind velocity; Rain: Average precipita Coefficients: Estimate S (Intercept) 123.118333 Temp Man Wind Rain 1.611436 0.025476 3.630245 0.524235 12:09 AM 4/26/2016 Ask me anything

Explanation / Answer

answer: SO2 pollution was related positively to number of factories ,rain and negatively to temperature,wind

(9) answer (d)

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