This paper describes our experience teaching S-Plus to first year computer and mathematical science students. We explain the reason for selecting S-Plus as the statistical package for our students and describe the material prepared to introduce the package and how it was presented. We also outline the problems that students experienced, analyse the reasons for these problems and the ways we are attempting to overcome these.
We attempt to use simulation to teach confidence interval for the slope parameter and prediction interval for the future observation in the simple linear regression model. Computer program in JAVA is written to illustrate the simulation in a step-by-step manner. As the observation vector is being generated, the scatter diagram, fitted line and confidence interval will be displayed. Histograms for the individual observations will be built up slowly and the proportion of confidence intervals covering the true value will be updated .The students will realize that the proportion tends to the desired value. Similarly prediction interval can be taught by using simulation .The students will realize that the average value of the proportion of the future observations falling inside the prediction interval tends to the desired value.
In basic Statistics classes, we are often interested in "Tree Diagrams", which provide a visual way for our students to compute how many ways various events can occur. One special example of this is the US National Collegiate Association of America (NCAA) Basketball tournament, which takes place in March of each year. Fans get caught up in "March Madness," and enjoy trying to predict the "Final Four". In this paper, we discuss many aspects of this tournament, including sharing of what the Tree diagram looks like, various probabilities of what different teams will do, and making predictions about what will happen in the First Round and beyond.
Undergraduates at California State University, Chico's College of Agriculture do experimental research including data analysis. Desire to see if treatments differ, motivates students to learn inferential statistics. Students analyze data with ANOVA programs written for Microsoft Excel. These programs return an analysis with one or at most a few mouse clicks; they handle missing data - a problem in real world experiments. In statewide science competitions, our students routinely place first or second.
For the last decade, internationally, there have been calls for reform in statistics education. These calls for reform have emphasised that teaching should use real data, active learning, technological tools and statistical thinking. A way of incorporating all these aspects into a statistics course is through the use of projects. This paper will summarise the calls for reform and the use of projects by others along with projects that have been used by the author in courses that he teaches in experimental design and multiple regression. The emphasis here has been to include a full problem solving cycle, from problem definition to communicating findings and reflecting on the process. Feedback from the students will be included.
The activities in this book introduce students to simple random sampling, sampling techniques, and simulation as a tool for analyzing both categorical and numerical data. Scenarios probe topics of interest to high school students, including possible workplace discrimination against women and links between vegetarian diets and blood cholesterol levels. As students work, they learn what makes a well-designed study; how to distinguish among observational studies, surveys, and experiments; and when statistical inference is permissible. The supplemental CD-ROM features interactive electronic activities, master copies of activity pages for students, and additional readings for teachers.
In this article data from Old Faithful geysers are introduced to highlight the important role that variation should play in our teaching of statistics. Our past teaching may have overemphasized the role of centers to the neglect of issues of spread and variability.
This paper examines the role of variation in statistics education and describes a chance and data unit with a focus on variation that has been conducted with three high school mathematics classes.
Statistics is taught as a core course in the Management programmes leading to the degree of Master of Business Administration (MBA) or an equivalent degree in various Universities and Management Institutes in India. As a part of this course, Probability Theory, and Probability distributions are covered. The students who are admitted to this course are drawn from various disciplines; their level of understanding of mathematical concepts is not uniform, and hence, introducing concepts of the above topics need very careful planning and execution. In this paper, we outline some approaches generally used in teaching these courses, and compare the effectiveness of these approaches. We propose the use of case-based approach to teach some of the basic concepts in Statistics. We also discuss a specific case problem and discuss how this case problem can be effectively used to introduce the concept of Probability and Probability distributions. This method has been found to be quite useful in teaching Statistics in Executive Development Programmes also.
This paper will describe a project designed to enhance the numeracy skills of students at two educational levels - elementary and undergraduate. Under the guidance of the university students, students in grades four through six will formulate a research question, gather the appropriate data and summarize the data using graphs. The graphs along with a written summary of the project will be displayed in a poster, which will be sent to the national poster competition sponsored by the American Statistical Association.