The experiment was established to determine the effect of the C2 F6 flow rate on the uniformity of the etches on a silicon wafer used in integrated circuit manufacturing. All of the runs were made in random order. Data for two rates are as follow: C2F6 Flow (SCCM) Uniformity Observation 100 2.7 4.6 2.6 3.0 3.2 3.8 200 4.6 3.4 2.9 3.5 4.1 5.1 1) Does the C2 F6 flow rate affect average etch uniformity? Use α = 0.05 2) Create a boxplot and do the boxplot agree with your previous conclusion?
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
The experiment was established to determine the effect of the C2 F6 flow rate on the uniformity of the etches on a silicon wafer used in integrated circuit manufacturing. All of the runs were made in random order. Data for two rates are as follow:
| C2F6 Flow (SCCM) |
Uniformity Observation | |||||
| 100 | 2.7 | 4.6 | 2.6 | 3.0 | 3.2 | 3.8 |
| 200 | 4.6 | 3.4 | 2.9 | 3.5 | 4.1 | 5.1 |
1) Does the C2 F6 flow rate affect average etch uniformity? Use α = 0.05
2) Create a boxplot and do the boxplot agree with your previous conclusion?
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