This paper simply contains a long list of teaching aids that are available for sale from various companies such as transparencies, audio tapes, film strips, slides, films, video tapes, course packages, and probability devices.
Describes the PMOSE/IKIRSCH document readability formula for documents. Main document components in which the formula was based; Graphic documents; Entry documents; Density of documents; Usefulness in measuring document complexity.
For many years the Royal Statistical Society has had an Ordinary Certificate in Statistics as a first qualification in statistics. In 2000 the three authors worked with colleagues from the National Statistical Office (NSO) in Malawi and from Chancellor College, University of Malawi, to develop a parallel course in Key Statistical Skills for clerks at the NSO. This course emphasizes the practical nature of statistics and develops skills in teamwork, communication and project work as well as including some extra statistical content in demographic and economic statistics. The first students took the courses in 2000/2001. The authors will report on the experience and the positive gains in tailoring courses for particular student needs.
Many students have difficulty seeing the conceptual 'link' between bivariate data displayed in a scatterplot and the statistical summary of the relationship, r. This article shows how to teach (and compute) r such that each datum's 'direct' and 'indirect' influences are made apparent and used in a new formula for calculating Pearson's r.
This paper describes a course that was developed to teach statistics to students majoring in Psychology and Politics. There were several interesting aspects to this course. Firstly each lecture contained between 550 and 800 students. Secondly those students were almost uniformly negatively disposed to Statistics prior to the beginning of the course. Thirdly we were required to provide an introduction to Statistics in just 12 lectures, each of 50 minutes duration. Constrained, we were forced to think deeply about what we want to provide to students in an Introductory Statistics course. Making use of simulations and the internet, we chose to emphasise concepts and critical thinking and supported these with examples which had direct relevance to our students. Restricted to 12 lectures, we learned to make optimum use of each lecture. Can a short course like this act as a useful pre-cursor to the standard Introductory Statistics course?
Confidence interval estimation is a fundamental technique in statistical inference.<br><br>Margin of error is used to delimit the error in estimation. Dispelling misinterpretations<br><br>that teachers and students give to these terms is important. In this note, we give examples<br><br>of the confusion that can arise in regard to confidence interval estimation and margin of<br><br>error
Formal calculations often do not yield insight into "how your model solves your problem". A strategy in connection to the birthday problem is discussed that does give intuitive orientation. Furthermore some situations do not seem "stochastical" at first sight but can be structured by stochastical models. Even in these models do not fit the situation you can get sensible results from that models. The birthday problem is shown to be a problem of that type.
Many elementary statistics textbooks recommend the sign test as an alternative to the t-test when the normality assumption is violated. This recommendation is not always warranted, as we demonstrate by extending previous studies of the effects of skewness, kurtosis, and shifting of the location parameter on the size and power of the t- and sign tests for the one-sample case. For skewed populations our simulations reveal that the power of the t-test can actually be higher than that of the t-test for a normal parent population when the location parameter is shifted in the opposite direction of the skewness of population. In that same instance, the power of the t-test is also significantly greater than that of the sign test. Furthermore, our simulations reveal that for low-kurtosis populations the power of the t-test is again greater than that of the sign test.
This paper addresses the problem of generating a large number of data sets for classes of students that exhibit certain characteristics but which are sufficiently different to minimize the possibility of plagiarism. A number of R functions are provided to perform the production of the data and the answers to the relevant data.