Minitab Design of Experiments Contest: Projects Reveal Power of DOE Tools
Minitab Design of Experiments Contest: Projects Reveal Power of DOE Tools
Power and Sample Size – Your Insurance Policy for Statistical Analysis (Insights America 2019)
When we do statistical analyses, like hypothesis testing and design of experiments, we are using a sample of data to answer questions about all of our data. The reliability of these answers is affected by the size of the sample we analyze. To minimize the risk of doing unreliable statistical analysis we can use the Power and Sample size before collecting any data to determine how much data is needed to have a good chance of finding that effect, if it exists. The minimum recommended value for this is 80%.
You Use Minitab. Your New Job Doesn't (YET). What Do You Do? (Insights America 2019)
Rafael's previous employers used Minitab, giving him ample opportunity to figure out how to define experiments and variables to optimize detergent formulas most effectively. But Rafael's new employers didn't use Minitab. His boss challenged him to prove results before considering the investment.
Guest Post: It’s Tough to Make Predictions, Especially about the Future (even with Machine Learning) (Insights America 2019)
At its core, all Machine Learning algorithms follow a two-part process. First a sequence of increasingly complex functions is fit to part of the data (training data set). Then each model in the sequence is evaluated on how well it performs on the data that was held out (the holdout set).
Concluding Our Golf DOE: Time to Quantify, Understand and Optimize (Insights America 2019)
Last week on The Minitab Blog, we used Minitab Statistical Software to review analysis of covariance (ANCOVA) and blocking variables in our ongoing design of experiment (DOE) on how to get the longest drive in your golf game. Now let’s finish it. We’re ready to review and present our results.