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1) The probability that this confidence interval captured the true average difference is 0 or 1 90% of all confidence intervals done this way would correctly capture the true average difference We cannot show with 90% confidence that the true averages are statistically different We are 90% confident the true average difference is between -1.47 and 5.83 There’s a 90% probability the next confidence interval captures the true average difference 2) H0: µd ≥ 0 Ha: µd < 0 α = 0.05 t=(37.77-38.44)/(2.39/sqrt(49)) = -1.96 0.025 < p-value < 0.05 Reject Our data shows the sun is lowering the hardness of the bricks 3) 142 142 1 142 200 200 1.555 =(0.66, 0.76) 200 200 4) 0.005=2.576s * sqrt( .5*(1-.5)/n ) N=(2.576/0.005)2*.5*(1-.5) = 66.357.76 Need 66358 people 5) H0: µ=16 Ha: µ≠16 α = (somewhere between 0.08 to 0.15) t=2.2 (accept 2 to 2.5) pvalue should be around 0.014x2 = 0.03 Reject The average temperature for a CSU student to stay home is significantly different from 16 6) Cannot do 7) 150 +- 2.398 * 25/sqrt(10) = (131.04, 168.95) 8) H0: Time is independent of light running Ha: Time is related to light running α = 0.05 17.67 20.32 22.32 25.67 1.06 0.918 0.836 0.730 z 22 40 16 46 0 38 38 38 38 1 1 86 86 86 86 40 46 1.88 0.05 < p-value < 0.10 p-value =2*0.0301 = 0.0602 Fail to Reject We cannot show the time of day affects whether people run the light 9) 1.183 +- 1.99 * 0.116974 = (1.597, 2.062) We are 95% confident that for every dollar increase an engineering parent has in starting salary the child engineer’s starting salary will go up by 1.597 to 2.062 dollars. Bonus: Groups Error Total DF SS MS F 4 15 19 24 30 54 6 2 3