1. The following data set is derived from two different analytical methods analyzing the same samples. The samples contain different concentrations of acetylsalicylic acid (ASA) added to blood. The two analytical methods are chromatographic methods and only differ in the oven temperature (35 C vs. 45 C) while all other parameters are held constant. Each sample is analyzed 3 times. [15 points]

	Detector signal (in mV)
Spiked ASA concentration (in mg/L)	Method 1 (35 C)	Method 2 (45 C)
0.25	20	18	21	25	23	28
0.5	33	31	32	41	38	39
1.0	44	48	45	91	87	95
2.0	71	75	73	136	145	139
4.0	125	119	131	181	172	175

1. Plot the two linear regression models on one set of axes. Then calculate coefficients of determination for each of the two methods (note: you can use Microsoft Excel or any other program that is able to calculate simple linear regression models. If you do, please provide the data file in addition to the answer). Which of the methods would you prefer for the analysis of ASA samples over a concentration range of 0.25 to 4 mg/L?
2. Calculate the 95% confidence intervals for the slopes of each of the two regression models. Do these confidence intervals overlap? What conclusions can you draw from the confidence intervals?
3. Test the hypothesis that the two slopes are not significantly different from each other. In order to do so, consider that the each of the slopes is a variable that has a mean and a standard deviation - you can use a test that has been discussed in former modules to compare the two slopes with each other.