This software uses spreadheets, data tables, and numerous graphing capabilities to help students learn important statistical concepts while handling all the calculations. This student version of JMP combines classical statistics with state-of-the-art interactive graphics that cover many functions simultaneously. Spinning plots, bi-plots, and scatterplot matrices created with JMP IN make it easier for students to identify structure and spot outliers. It provides an array of statistical analysis tools in an easy-to-use format and aims to make creating pie charts, bar charts, line charts, two- and three-dimensional scatterplots, tables, Pereto and quality-control charts simple. The software includes student-level exercises and unlimited data sets.
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Editions-Typ
ISBN-13
978-0-534-35430-5 (9780534354305)
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Schweitzer Klassifikation
Part I JMPing IN with both feet: 1. Jump Right In. First Session. Modelling Type. Analyze and Graph. Getting Help: The JMP Help System. 2. JMP Data Tables. The Ins and Outs of a JMP Data Table. Moving Data and Results Out of JMP. Juggling Data Tables. The Group/Summary Command. 3. Calculator Adventures. The Calculator Window. A Quick Example. Calculator Pieces and Parts. Terms Functions. Conditional Expressions and Comparison Operators. Summarize Down a Column or Summarize Across Rows. Random Number Functions. Parameters. Tips on Building Formulas. Caution and Error Messages. Part II Statistical sleuthing: 4. What are Statistics? Ponderings. Preparations. Statistical Terms. 5. Univariate Distribution: One Variable, One Sample. Looking at Distributions. Review: Probability Distributions. Describing Distributions of Values. Statistical Inference on the Man. Special Topic: Testing for Normality. Special Topic: Simulating the Central Limit Theorem. 6. Differences Between Two Means. Two Independent Groups. Testing Means for Matched Pairs. Review. A Nonparametric Approach. 7. Comparing Many Means: One-Way Analysis of Variance. What is a One-Way Layout? Comparing and Testing Means. Special Topic: Adjusting for Multiple Comparisons. Special Topic: Power. Special Topic: Unequal Variances. Special Topic: Nonparametric Methods. 8. Fitting Curves Through Points: Regression. Regression. Why Graphics are Important. Why It's Called Regression. Curiosities. 9. Categorical Distributions. Categorical Situations. Categorical Responses and Count Data: Two Outlooks. A Simulated Categorical Response. The Chi-Square Pearson Chi-Square Test Statistic. The G-Square Likelihood Ratio Chi-Square Test Statistic. Univariate Categorical Chi-Square Tests. 10. Categorical Models. Fitting Categorical Responses to Categorical Factors. Correspondence Analysis: Looking at Data with Many Levels. Continuous Factors for Categorical Responses: Logistic Regression. Special Topics. Surprise: Simpson's Paradox: Aggregate Data versus Grouped Data. 11. Multiple Regression. Parts of a Regression Model. A Multiple Regression Example. Special Topic: Collinearity. Special Topic: The Case of the Hidden Leverage Point. Special Topic: Mining Data with Stepwise Regression. 12. Fitting Linear Models. The General Linear Model. Two-Way Analysis of Variance and Interactions. Optional Topic: Random Effects and Nested Effects. 13. Bivariate and Multivariate Relationships. Bivariate Distributions. Correlations and the Bivariate Normal. Three and More Dimensions. 14. Design of Experiments. Introduction. Generating and Experimental Design in JMP. Two-Level Screening Designs. Screening for Main Effects: The Flour Paste Experiment. Screening for Interactions. Response Surface Designs. 15. Statistical Quality Control. Control Charts and Shewhart Charts. The Control Chart Dialog. Pareto Charts. 16. Time Series Analysis. Introduction. Graphing and Fitting by Time. Lagging and Autocorrelation.
