lab5.pdf - HaiLam Nguyen \u2013 V00914037 1 > rm(list = ls > radiation.data = read.table(file =\"radiation header = T > year = radiation.data$Year > dose =

lab5.pdf - HaiLam Nguyen u2013 V00914037 1 > rm(list = ls...

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HaiLam Nguyen V00914037 Max
0.4672 F-statistic: 9.769 on 1 and 9 DF, p-value: 0.01221 Letβbe the slope of the estimated regression line. Test statistic:H0: β= 0 H1: β0.01 < p-value < 0.05, there is moderate evidence against H0, that means there can have no linear relationship between X and Y. 3. Point estimate for α: -108373.62 Point estimate for β: 57.58 4. > confint(my.model, level = 0.95) 2.5 % 97.5 % (Intercept) -192225.01169 -24522.22467 year 15.90623 99.25741 95% CI on α: (-192225.01169, -24522.22467) 95% CI on β: (15.90623, 99.25741) 5. > predict(my.model, newdata = data.frame(year = 2012), interval = "confidence") fit lwr upr 1 7481 7349.21 7612.79 Point estimate for the mean Total Air KERMA for 2012: 7481 95% confidence interval: (7349.21, 7612.79) 1 0 6. > predict(my.model, newdata = data.frame(year = 2012), interval = "prediction") fit lwr upr 1 7481 7024.467 7937.533
Point estimate for the Total Air KERMA for 2012: 7481 95% prediction interval: (7024.467, 7937.533)

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