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Developmental education has the mission of enabling underprepared students to acquire the capabilities necessary for college success. A growing number of research studies document its failure, however; specifically, approximately two thirds of community college students referred to a remedial mathematics sequence do not complete it. In response to these findings, The Carnegie Foundation for the Advancement of Teaching, with the Charles A. Dana Center as a principal design partner, is launching a comprehensive initiative to create two new pathways, the Statway and the Mathway, to enable developmental mathematics students to complete a credit-bearing, transferable mathematics course in one academic year while simultaneously building skills for long-term college success. The primary curricular goal of the Statway course sequence is to develop the mathematical proficiency of students pursuing non-STEM academic and occupational programs, with a special focus on statistical literacy. This paper describes the research-based Statway design and its intended learning outcomes, the processes and participants involved in its development, and the challenges of implementation. Appended are: (1) Statway Collaboratory Colleges; (2) Mathway Collaboratory Colleges; and (3) Members of the Carnegie Committee for Statistics Learning Outcomes (CCSLO). (Contains 4 figures and 3 footnotes.)

The National Centre for Vocational Education Research (NCVER) was asked by Technical and Further Education (TAFE) Directors Australia to consider, in a discussion paper for their conference held on the Gold Coast in September 2009, how a "tertiary education" sector impacts on the way people think about research and statistics. While a tertiary education focus would be a forward-looking step, it is important that both vocational education and training (VET) and higher education issues receive due attention. Individuals need to build on the good work done for the VET sector rather than subsume it in any sense. What is needed to make sense of the education, participation and achievement of individual students is an integrated tertiary education statistical system. This would require a common core set of standards. It would be relatively straightforward to populate a tertiary education student database from different collections. This database would then be a resource for policymakers and researchers. An integrated approach is required, not an approach which appends higher education statistics to the VET statistics or vice versa.

Apprentice and trainee data are reported by the State and Territory Training Authorities to the National Centre for Vocational Education Research (NCVER) on a quarterly basis, starting at the September quarter of 1994. The set of data submitted that quarter is referred to as Collection 1. The sets of data submitted in subsequent quarters are referred to as Collection 2, Collection 3 and so on. At the time of writing, the set of data being submitted is for the June 2009 quarter and is referred to as Collection 60. Of particular interest is the numbers of contracts of training that commence, complete, cancel/withdraw, re-commence, expire or suspend and the time at which these events occur (referred to as the "date of effect"). From these events, the number of contracts in training at a given time can be calculated. Between the occurrence of one of these events and the appearance of the corresponding datum in the national collection, there is a chain of administrative processes that must be followed. It is not unusual for some time to elapse before information about events appears in the national collection. These time gaps are referred to as "reporting lags". Thus, data about events occurring in a given quarter might require several collections to be completely reported. As a result, accurate counts take time to accumulate. However, waiting for the all the data to be submitted reduces their usefulness. In order to get timely information that can be used for monitoring apprentice/trainee activity and formulating policy, a reliable estimate of the "final" counts is required as soon as possible after the quarter in which the events occur. The current method of calculating estimates from the Apprentice and Trainee collection was endorsed in September 2004 by the National Training Statistics Committee. The purpose of this technical paper is to describe: (1) the way data accumulate over many collections; (2) how items derived from the data change as the data accumulates; (3) the endorsed estimation method (developed from the analysis of the above); (4) the formulae for calculating the required estimates; and (5) potential weaknesses in the method. Supporting data is appended. (Contains 4 tables and 8 figures.) [For the accompanying report, "Apprentices and Trainees: September Quarter 2009", see ED508817.]

The Decennial Census is the most important data collection activity undertaken by the U.S. federal statistical system. Because census data are used to apportion Congress and draw redistricting lines for thousands of state and local single-member districts to meet the one-person/one-vote guidelines, the census is at the heart of the political system. Also, census data are used to distribute more than $400 billion in federal funds each year, and they are widely used by other government statistical agencies to calculate rates or design surveys. Children are the age group most often missed in the Decennial Census--the reasons range from their living in hard-to-count neighborhoods to the fact that the census form only has space for complete demographic information on six household members. The fact that children are the age group missed most often in the Decennial Census comes as a surprise to many people, even those who have closely followed census issues. Despite the long-standing problem of children being missed in the Decennial Census, little has been done to examine this issue. Missed children might be referred to as the "overlooked undercount" because the undercount of children has been a persistent problem that has been given relatively little attention over time. The high undercount of children challenges the image that the undercount is made up mostly of young adults and people who dodge the census-takers for nefarious reasons. Unlike adults, who may bear some responsibility for making sure they are counted in the census, children are dependent on others to make sure they are included. Yet in 1980, 1990, and 2000, Census Bureau data show children, particularly young children, are one of the groups most likely to be missed in the census. This publication provides some background and information on the undercount of children, describes some theories about why children are missed in the census, and outlines a few ideas for reaching the parents of young children with a message about the importance of being counted in the census. (Contains 2 figures, 1 box, 10 tables and 37 endnotes.)

Confidence intervals are beginning to play an increasing role in the reporting of research findings within the social and behavioral sciences and, consequently, are becoming more prevalent in beginning classes in statistics and research methods. Confidence intervals are an attractive means of conveying experimental results, as they contain a considerable amount of information in a concise format. The objectives of this study are to (1) show that the theory of conceptual metaphor as delineated in contemporary embodied cognition is a useful framework for describing statistics students' conceptions of confidence intervals; and (2) provide empirical evidence from discourse and gesture that graduate students in social science use at least two competing conceptual metaphors for confidence limits that have important implications for the understanding and application of statistics and for the reform of statistics education. In the first metaphor--Confidence Intervals Are Changing Rings Around a Fixed Point ("Changing Ring metaphor")--confidence intervals are moving disks of various diameters covering a fixed but unknown point, like horseshoes of varying widths pitched at a fixed stake. Key to this correct conceptual metaphor is that the interval is a property of a sample but not of the population. Here, the diameter of the disk (i.e., the length of the confidence interval) changes from sample to sample, whereas the location of the stake (i.e., the population parameter or population mean) is fixed across samples but generally unknown. In contrast, the second metaphor--Confidence Intervals Are Changing Points on a Fixed Disk ("Fixed Disk metaphor")--conceptualizes confidence intervals as fixed-diameter disks onto which successive points are placed. In this incorrect metaphor, the population parameter can change from sample to sample. The interval is of a fixed length, and each experiment results in placing a new parameter somewhere onto the fixed-diameter disk. One possible source of this second metaphor is a suspected confusion between acceptance regions in hypothesis testing and confidence intervals, concepts that tend to be taught in close proximity to one another in statistics textbooks. The Fixed Disk metaphor will generally lead to a misinterpretation of the confidence interval that results in inaccurate problem solving. By better understanding students' mental representations of confidence intervals and appealing to the metaphors they convey, the authors hope to improve both statistics instruction and education researchers' uses of statistical tests. Interview items are appended. (Contains 5 tables and 4 figures.)

This study reports on five disciplinary case studies that explore academic value systems as they influence publishing behavior and attitudes of University of California, Berkeley faculty. The case studies are based on direct interviews with relevant stakeholders--faculty, advancement reviewers, librarians, and editors--in five fields: chemical engineering, anthropology, law and economics, English-language literature, and biostatistics. The results of the study strongly confirm the vital role of peer review in faculty attitudes and actual publishing behavior. There is much more experimentation, however, with regard to means of in-progress communication, where single means of publication and communication are not fixed so deeply in values and tradition as they are for final, archival publication. We conclude that approaches that try to "move" faculty and deeply embedded value systems directly toward new forms of archival, "final" publication are destined largely to failure in the short-term. From our perspective, a more promising route is to (1) examine the needs of scholarly researchers for both final and in-progress communications, and (2) determine how those needs are likely to influence future scenarios in a range of disciplinary areas. (Contains 11 notes.)

This document contains the following nine appendixes of the main report, "What Does It Cost to Educate California's Students? A Professional Judgment Approach. Technical Report. Getting Down to Facts II": (1) Professional Judgement Panel General Instructions; (2) Professional Judgement Panel. Task Instructions; (3) School Resource Profiles; (4) Suggested Reading for Professional Judgement Panelists; (5) Professional Judgement Panelist Information; (6) Program Design Documents; (7) Professional Judgement Panelist Cost Estimates; (8) Descriptive Statistics; and (9) Explanation of Update to Study Findings. [For the main report, see ED594739.]

"SERJ" has provided a high quality professional publication venue for researchers in statistics education for close to a decade. This paper presents a review of the articles published to explore what they suggest about the field of statistics education, the researchers, the questions addressed, and the growing knowledge base on teaching and learning statistics. We present a detailed analysis of these articles in order to address the following questions: What is being published and why, who is publishing research in "SERJ," how is the research being carried out, and what do the results suggest about future research? Implications for future directions in statistics education research are suggested. (Contains 9 tables and 3 figures.)

Student pathways through the American higher education system are complex and entail more than the choice between continuation and dropout. The four-year college system requires students seeking a bachelor's degree to pass through a series of transitions that are marked by the achievement of credit thresholds in each year of study. At those junctures students make critical decisions about their progress: whether to enroll for sufficient credits to ensure timely completion, whether to enroll for fewer credits, or whether to leave school for a limited period of time. This project overcomes the simplistic view of discrete choices between enrollment and nonenrollment and takes a close look at the cumulative nature of the attainment of U.S. students at four-year colleges and the social inequalities arising in this process. Detailed transcript data from the National Educational Longitudinal Study (NELS-88) and multinomial transition models provide evidence on the shape of and social inequality in four-year college careers. We describe distinct trajectories through college and show that they strongly depend on students' decisions at earlier stages of their college careers. Transitions through college are also found to be strongly related to students' socioeconomic backgrounds. In addition, we show that the penalties incurred from unfavorable earlier choices is greater for disadvantaged students. By fully appreciating the cumulative nature of educational pathways through college we provide an important new view on the complex routes to college completion and trace an important source of the socioeconomic gap in college completion. The relatively rigid structure of the U.S. four-year college system appears to produce strong path-dependent and status dependent cumulative advantages for high-status students. Appended are the following tables: (1) Variable Descriptions; (2) Multinomial Regressions (Odds Ratios); and (3) BA Completion (Odds Ratios). (Contains 4 tables, 4 figures, and 10 footnotes.) [An earlier version of this paper was presented at the spring 2008 conference of the Research Committee on Stratification and Mobility (RC28) in Florence, and the 2009 annual meeting of the Sociology of Educational Association (SEA) in Monterey.]

This chapter considers the design of incentive pay systems for teachers and principals and the challenges facing policy makers who seek to design them. The author argues that policy makers must direct the efforts of teachers and principals toward schools' mission--the acquisition of skills and knowledge among children--and must find ways to link the compensation of teachers and principals to the value of the educational services provided by their schools. However, the nature of the educational process creates at least three important challenges for those who design incentive systems for educators. Even when reliable measures of student achievement are available, it is difficult to value the outputs of schools and also difficult to identify whom within different schools is responsible for the observed variation in the outputs of schools. Further, the process of assessing achievement under high-stakes may create undesirable re-allocations of resources among various types of learning activities within schools. The author's goal is to explain and analyze how these challenges affect the design of incentive systems for teachers and principals. (Contains 1 table and 19 footnotes.)

This paper discusses the three hypothetical market baskets of goods and services for which the Bureau of Labor Statistics publishes annual cost estimates. This program is referred to as the standard budgets or family budget program. The family budget program provides: 1) estimates of budget levels originally constructed to represent standards of living; 2) interarea indexes of "living costs" based upon these budget estimates; and 3) adjustment factors to convert the budgets for other family sizes and types. Attention is given to the limitations of the family budgets as measures of income adequacy and to their use as indexes of interarea cost-of-living differences. Briefly, the general limitations of the budgets program with respect to defining poverty are: 1) as measures of income adequacy, 2) as measures of interarea cost of living differences, and 3) as adjustment of factors for various sizes and types of families. The paper also discusses the manner of living represented by the market baskets program, price measurement problems, geographic cost of living comparisons, and equivalence scales. In addition, it includes a short section which discusses areas for future research in this program. (Author/AM)

Experimenters sometimes wish to estimate for a particular dependent variable the proportion of total group variance that is associated with mean differences among fixed treatments or subject classifications. Hays (1981) represents this proportion by the parameter omega squared. A point estimate may be easily computed as a function of the number of treatments, the total sample size, and the mean squares between and within treatments. This paper presents tables which facilitate the construction of 90 or 95 percent confidence intervals for omega squared. (Author)

Bayesian statistical inference is unfamiliar to many educational evaluators. While the classical model is useful in educational research, it is not as useful in evaluation because of the need to identify solutions to practical problems based on a wide spectrum of information. The reason Bayesian analysis is effective for decision making is that it defines probability as a measure of opinion or belief, rather than as long-term frequency. Defining probability as a measure of opinion or belief enables the Bayesian investigator to consider a wider range of information than is possible with the traditional model. Personal expertise, logical analysis, and soft data from a wide variety of sources serve to shape opinion about a state of nature, with experimental data providing additional information either for or against the prior opinion of the evaluator. In classical statistics, prior knowledge or opinion is ignored. However, when practical decisions must be made the Bayesian stresses that all knowledge should be brought to bear on the problem rather than just an isolated set of data. Because of the decision-making orientation of the evaluator, the Bayesian model should be considered as an alternative to classical inference. Since the Bayesian model views probability as a measure of opinion rather than as a long-term frequency, the statistical requirements for it are actually greater than for the classical statistician. Use of a wider range of distributions than with classical statistics demands more statistical skills than many evaluators currently possess. However, the questions raised by the Bayesian model are useful even if the model is not totally adopted. (Author/RC)

The testing of research hypotheses is directly comparable to the dichotomous decision-making of medical diagnosis or jury trials--not ill/ill, or innocent/guilty decisions. There are costs in both kinds of error, type I errors of falsely rejecting a null hypothesis or type II errors of falsely rejecting an alternative hypothesis. It is important to consider the power of a statistical test (that is, the likelihood of avoiding type II errors) as well as the significance level (the likelihood of avoiding type I errors) before an experiment is begun. Techniques for estimating the power of a statistical test for a particular experimental design are presented. (CTM)

Informality is a dynamic and multidimensional concern that demands gender-sensitive data. In 2018, globally, more than 60% of employment was informal. However, global averages hide that in more countries the share of women in informal employment exceeds that of men. Also, women in the informal economy are often in the most unprotected situations - as domestic workers, home-based workers and contributing family workers - where a lack of visibility can increase their vulnerability. The ILO and its partners are working to engender informality statistics to improve gender data and support countries to respond to data needs on women's economic empowerment. This working paper was written to support the ILO Working Group for the Revision of the standards for statistics on informality. It explores the demand for gender data on informality and the measurement challenges faced. The paper highlights the opportunities emerging from the revision of statistical standards on informality that are set to be adopted in 2023. [ABSTRACT FROM AUTHOR]

Summarizes 19 papers presented at the Fourth International Conference on Teaching Statistics held in Morocco, July 1994. Papers presented were in five categories: (1) empirical studies on students' conceptions; (2) theoretical papers on teaching and learning; (3) assessment; (4) using computers in teaching probability and statistics; and (5) data analysis. (MKR)