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We identify the student characteristics most associated with success in an introductory business statistics class, placing special focus on the relationship between student math skills and course performance, as measured by student grade in the course. To determine which math skills are important for student success, we examine (1) whether the student has taken calculus or business calculus, (2) whether the student has been required to take remedial mathematics, (3) the student's score on a test of very basic mathematical concepts, (4) student scores on the mathematics portion of the ACT exam, and (5) science/reasoning portion of the ACT exam. The score on the science portion of the ACT exam and the math-quiz score are significantly related to performance in an introductory statistics course, as are student GPA and gender. This result is robust across course formats and instructors. These results have implications for curriculum development, course content, and course prerequisites.

Fostering economic development and entrepreneurship is a crucial goal for every contemporary economy. Economic activity and business dynamics can be measured in the various ways, but recently the use of some demographic methods in measuring economic activity has been introduced. During the last few years there is a growing demand for data on business/enterprise demography, including enterprise births, deaths and survivals. Moreover, to create the best conditions for successful entrepreneurship, policy makers require statistical data on enterprise births, survivals of born enterprises and enterprise deaths as well as analysis of their effects on overall economic conditions. This paper surveys the methodology recently developed by Eurostat and aims to describe the current level of development of business demography in Croatia. Next, the assessment of enterprise demography data available in Croatia today is presented. Data are collected from Register of Business Entities conducted by Croatian Central Bureau of Statistics. After the examination of data sources, selected methods of demographic analysis are applied. Data are analyzed by economic activity, employment size and by counties. Cross-country analysis between Croatia and some old and new EU members is also conducted using harmonized data collections. At the end, future development of enterprise demography in Croatia is considered.

More and more business professors are integrating technology into their courses to create a more stimulating learning environment and develop better communication channels between students and instructors. Online lessons, whether used as a study aid in the hybrid classroom or, as a complete package for the distance learner, create additional workloads for instructors who are willing to commit to the online environment. Any tool that can ease the creation process is a welcome addition to even the most technologically savvy professor. This paper shows how a statistics application program, such as PHStat, can be fully integrated into a complete online reenactment by using a video/sound capture program such as Camtasia Studio 2.

In many management programs at the undergraduate level, a certain number of courses are scheduled as large classes where students have heterogeneous knowledge, motivations, and learning styles. In Grenoble Ecole de Management, we have tried, like many others, to apply the various recommendations provided by Education Science specialists. We have also used Information and Communication Technology (ICT) to support our courses, hoping that it would increase flexibility and allow us to be more learner-centered. However, we were not entirely satisfied with our results. In the first part of this chapter, we describe this initial environment and the main issues we had to address. In a second part, we present our new pedagogical model. For the last two years, we have experimented with an innovative two-phase organization of a Business Statistics course. The first phase allows to deliver the basic content

Statistics is an essential part of an undergraduate business degree program. Undergraduate institutions commonly require prerequisite courses to ensure that students are prepared to learn the material in the core courses. Presumably, successful completion of prerequisite courses should increase students’ confidence and performance in the core courses. Students often express fear and anxiety over quantitative and mathematics courses, and frequently object to the math prerequisite for the business statistics course, complaining that it only results in prolonging their degree program. The objective of this paper is to examine empirically whether the math prerequisites for the business statistics course help the learning experience. This study suggests that these prerequisites do help students at a four-year state institution with an open enrollment policy. Grades are used as the measure of performance for both the prerequisite and the core statistics courses. The findings confirm that prerequisites should be kept in place for the business statistics course.

Previous research has linked perfectionism to anxiety in the statistics classroom and academic performance in general. This article investigates the impact of the individual components of perfectio...

We compare students in online and lecture sections of a business statistics class taught simultaneously by the same instructor using the same content, assignments, and exams in the fall of 2001. St...

Fraudulence cases have happened all the time in business environments. The responsibilities of auditors are to prevent the swindling cases and to ensure that every operation conforms to regulations. In recent years, IT is adopted in business environments. Traditional approaches with paper operation using papers to be audit trails should be changed to EDP auditing. Typically, since auditors come from nonIT backgrounds, it's difficult for them to involve the area of EDP auditing. Furthermore, enterprise resource planning (ERP) is adopted competing with other opponents around the world. ERP makes the enterprise systems more complicate. Hence, auditors face an even big problem about how to audit in ERP environment. We propose a mechanism to structure rules of auditing information by mapping from business processes to data flow and data model. With our mechanism, auditors can directly obtain auditing information based on business process and containing data changing process.

This fully updated fourth edition of this popular guide introduces readers to the collection, uses, and interpretation of statistical data in the social sciences. Since it has been nearly 15 years since the third edition first appeared, this is a heavily updated edition. Separate chapters are the national economy, wealth, income, poverty, labor, business statistics, and public opinion polling, with a concluding chapter devoted to the common problem of ambiguity in social science statistics. Each chapter includes multiple case studies illustrating the controversies, overview of data sources including web sites, chapter summary and a set of case study questions designed to stimulate further thought, and detailed notes providing references for all the controversies discussed in the chapter.

This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

Arguments about using computer facilities to classroom teaching have gained a lot of attention over time. Using the computer facilities will be helpful to demonstrate real world applications, while poor data or inappropriate case studies might reduce the confidence in applying computer programs in classroom teaching. In this article we examine the results of using computer facilities to teach Business statistics to a group of Management students sampled from Krannert School of Management, Purdue University. This study shows that students are attracted to the interactive computer programs designed for the Business Statistics course, and students are more motivated to attend classes when using computer facilities are applied in teaching. Furthermore, computer programs help students to understand confusing topics (such as the Central Limit Theorem), and students feel that teaching them to use computer facilities really improves students' ability to apply similar programs in analyzing real world problems.

(2007). Essentials of Statistics for Business and Economics. The American Statistician: Vol. 61, No. 2, pp. 182-183.

Economic statistics and social welfare comparisons - a review measurement of inequality poor areas the demand for health services in a developing country - the role of prices, service quality and reporting of illnesses on mobility aggregation and econometric analysis of demand and supply spatial dependence in linear regression models with an introduction to spatial econometrics panel data methods econometric analysis in complex surveys information recovery in simultaneous equations' statistical models diagnostic testing in econometrics - variable addition, RESET and Fourier approximations applications of the bootstrap in econometrics and economic statistics detection of unusual observations in regression and multivariate data union-intersection and sample-split methods in econometrics with applications to MA and SURE models modelling economic relationships with smooth transition regressions modelling seasonality in economic time series nonparametric and semiparametric econometrics of panel data on calibration.

There are specific problems in statistical education in Croatia as a transition country. Being a part of former Yugoslavia she was communist country with specific system of secondary and university education, and at the same time the country in the process of economic development. Students from grammar schools come with much greater knowledge of mathematics than students from other secondary schools. The later face problems to understand mathematical foundations of statistics. In developing country the use of computers during pre-university education was scarce due to the shortage of money invested in computer technology so it is possible to find university student without any touch with computer in previous education. In the process of modern statistical education the role of computers becomes much more important, so the situation in Croatia is improving rapidly. There is a problem of so-called "computer culture" for general population. It is recommended not to use computers in statistical education from the very beginning, because studet must understand mathematical and statistical operations without computers. Some professors think that students must solve as many problems as they can without computers, and only after that to use it for computations on massive scale. The other problems in statistical education during Communist rule was the lack of some statistical techniques such as survey sampling, because it was politically unwise. Statistical methodology in e.g. business statistics was also unlike western standards, due to big difference in economic and political system. Now, after the fall od communism, Croatian economy as well as statistical education is approaching western style.

One-way analysis of variance generalizes two-sample comparison of means (as developed in Basic Business Statistics). Rather than be limited to two groups, a one-way analysis of variance (anova) allows the comparison of several groups, identifying which group (if any) has the highest or lowest mean value.

Corporate distress and relative predictions have been a major theme for numerous researchers and practitioners in the last decades. The relevant literature adopts a variety of terms to describe corporate distress. The most commonly used terms are “failure”, “insolvency”, “default” and “bankruptcy”. All of them assign economic and financial problems and although they are used somehow optionally, these terms provide a slightly different definition connected with the specific interest or condition of the firms under examination.

The following analysis revisits the Forbes executive compensation data that was studied in Classes 2 and 3 of Basic Business Statistics. Rather than simply characterize the variation in total compensation, this regression analysis builds a model that attempts to “explain” the differences in compensation. We have come a long way since that introductory material.

(2006). Statistics for Business and Economics. The American Statistician: Vol. 60, No. 4, pp. 342-343.

Historically, the phenomenal growth of statistics as a separate discipline of great ubiquity was motivated by the need to solve practical problems arising in social, biological and natural sciences. Statistical methodology as we practice today involves acquisition of data. extraction of available information and taking optimal decisions under uncertainty. That the role of statistics as the logic and science of solving problems in other disciplines and that continued advances in statistics depend strongly on research stimulated by and directed at problems in other disciplines are not fully reflected in the educational programs for statisticians at the universities. It is suggested that more emphasis should be given to the interface between statistics and other disciplines through data-centered training in statistics.

Introduction The prevalence and level of exposure for each assessed agent was estimated for every European member state and relevant industry. These estimates provided the basis for the heath impact assessment. Detailed exposure data were unavailable for many member states and industries. The strategies used to create these estimates using limited available data will be discussed using the estimates produced for respirable crystalline silica (RCS) as an example. Methodology For 18 out of 25 assessed agents data from the CAREX project were used to estimate exposure prevalence. The proportion of exposed workers in each industry was averaged across countries for which data from 2000 or later were available. The average proportion was multiplied by the number of employees in the industry in each of the remaining member states in 2006 (from the Structural Business Statistics and Labour Force Survey available from EUROSTAT) to estimate the number of exposed workers. For agents that were not included in CAREX, exposure prevalence was estimated using data from trade associations and other stakeholders; from available exposure databases; or by assuming that all workers in exposed industries were exposed. The level of exposure was assessed using data from the published scientific literature, European Risk Assessment Reports, exposure databases, and trade associations. Industries were classified as high, medium or low exposure and a representative geometric mean (GM) and geometric standard deviation (GSD) was selected for each “medium” and “high” exposure industry. The overall weighted GM and GSD for each substance was estimated across all medium/high exposed industries with Monte Carlo simulation. Discussion Due to limited data availability, estimates were conservative in every instance. Had more data been available both the prevalence and exposure level estimates may have been lower, demonstrating the need for exposure measurement data from industry to be made available for research.

Business majors at AACSB accredited schools are required to take undergraduate statistics. Much research has been done with various learning style models for students enrolled in core business courses such as accounting, management, economics, and finance. However, the author has found no research that attempts to quantify the effects of learning style for students in business statistics. This study demonstrates that learning style as measured using the VARK model has significant effects on numerous variables of interest including academic success, student perceptions of course and instructor and academic major. The effect sizes are standardised and may be compared across studies. These findings provide a rationale for the delivery of course content in various modes to optimise student experiences and success.

Early in this century American institutionists and members of the German historical school attacked—and rightfully so—neoclassical economic theory for not being quantitative. This deficiency bothered Ragnar Frisch and motivated him, along with Irving Fisher, Joseph Schumpeter, and others, to organize the Econometric Society in 1930. The aim of the society was to foster the development of quantitative economic theory—that is, the development of what Frisch labeled econometrics. Soon after its inception, the society started the journal Econometrica. Frisch was the journal’s first editor and served in this capacity for twenty-five years.