JMP is a user friendly statistical software package that puts advanced analytic capabilities within an easy-to-use graphical interface. JMP is different from other statistical programming packages such as SAS and R since a great number of sophisticated analyses are readily available without the need to write computer code. This wealth of available options and analyses can be overwhelming, so this course is designed to provide some guidance for users who are new to JMP.
This short course starts with basic data manipulation, and moves to some advanced features, including importing data, interactive GUI, descriptive statistics such as numerical summary, inferential statistics such as t-tests, ANOVA, and regression. We will supplement computer lab components with lecture components.
Four data sets will be used. One contains 408 students’ records with 19 variables related to their SAT scores. Another consists of 50 samples from each of three species of Iris with four different features measured (see plot). The third one “car physical data” has information about 8 variables on 116 car models. The last one is from a study of how fast the body can absorb and use up oxygen, which contains 31 observation and 9 variables. All four data sets can be found inside JMP as sample data.