05 t-TEST, 1-SAMPLE
In the fifth Minitab tutorial, we will accompany the heat treatment process of the skateboard axles and see how the so-called hypothesis test, t-test for one sample, can be used to find out whether the heat treatment process is set so that the skateboard axles achieve the required compressive strength. To achieve this, the skateboard axles undergo a multi-stage heat treatment process. Our task in this Minitab tutorial is, to use sample data and the hypothesis test t-test for one sample, to make a reliable recommendation to the production management, as to whether the current heat treatment process is sufficiently well adjusted, or whether the current process might even need to be stopped and optimized if our hypothesis test shows, that the required mean target value is not being achieved. In the core of this Minitab tutorial, we will experience how a hypothesis test is properly carried out on a sample, and check in advance whether our data set follows the laws of normal distribution. With the help of a so-called discriminatory power analysis, we will work out whether the sample size is large enough. By using the so-called density function and probability distribution plot, we will learn how to classify the t-value in the t-test, and also understand which wrong decisions are possible in the context of a hypothesis test. With the help of corresponding individual value plot, we will develop an understand the so-called confidence interval, in the context of the one-sample t-test.
MAIN TOPICS MINITAB TUTORIAL 05, part 1
MAIN TOPICS MINITAB TUTORIAL 05, part 2
MAIN TOPICS MINITAB TUTORIAL 05, part 3