Tham khảo tài liệu 'exploratory data analysis_20', kỹ thuật - công nghệ, điện - điện tử phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . Analysis of the Response Variable NIS7 SEMATECH HOME TOOLS Al s SEARCH SACK NEXT http div898 handbook eda section4 3 of 3 5 1 2006 9 59 10 AM . Analysis of the Batch Effect ENGINEERING STATISTICS HANDBOOK HOME TOOLS Ậ AIDS SEARCH BACK NỄXf 1. Exploratory Data Analysis . EDA Case Studies . Case Studies . Ceramic Strength . Analysis of the Batch Effect Batch is a The two nuisance factors in this experiment are the batch number and the lab. There are Nuisance Factor 2 batches and 8 labs. Ideally these factors will have minimal effect on the response variable. Bihistogram We will investigate the batch factor first. This bihistogram shows the following. 1. There does appear to be a batch effect. 2. The batch 1 responses are centered at 700 while the batch 2 responses are centered at 625. That is the batch effect is approximately 75 units. 3. The variability is comparable for the 2 batches. 4. Batch 1 has some skewness in the lower tail. Batch 2 has some skewness in the center of the distribution but not as much in the tails compared to batch 1. 5. Both batches have a few low-lying points. Although we could stop with the bihistogram we will show a few other commonly used two-sample graphical techniques for comparison. http div898 handbook eda section4 1 of 5 5 1 2006 9 59 11 AM . Analysis of the Batch Effect Quantile-Quantile Plot This q-q plot shows the following. 1. Except for a few points in the right tail the batch 1 values have higher quantiles than the batch 2 values. This implies that batch 1 has a greater location value than batch 2. 2. The q-q plot is not linear. This implies that the difference between the batches is not explained simply by a shift in location. That is the variation and or skewness varies as well. From the bihistogram it appears that the skewness in batch 2 is the most likely explanation for the non-linearity in the q-q plot. Box
