Search

This article proposes a way to make the business-statistics course more relevant to future managers by designing the course around the activity of problem solving. A structured problem-solving framework is proposed, and ways to teach a variety of data analysis tools in the context of problem solving are outlined. This design is appealing because it emphasizes the use of statistics and data analysis in an activity that is important to managers. Students can see how to use statistical thinking in a context that will be important in their future careers.

Introductory statistics courses should incorporate unstructured projects where students themselves generate the problems they choose to study, gather their own data, analyze the information using suitable computer software, and communicate their findings in a report. This article describes my experience with projects in the context of a large lecture course where projects are carried out in groups. Special problems that arise with group projects are discussed. Several successful student projects are described.

A survey of business schools was conducted to obtain information about the current state of the teaching of business statistics to students enrolled in M.B.A. degree programs. The survey was undertaken for and presented at a June 1986 conference on “Making Statistics More Effective in Schools of Business,” held at the University of Chicago's Graduate School of Business. Information was elicited concerning both the required statistics sequence and elective statistics courses for M.B.A. students, as well as computer usage in these courses. This article summarizes the information obtained from the survey.

A number of problems are faced today by those who are attempting to carry instruction in business statistics beyond the stage of the elementary course in method. In the first place, students do not learn in the elementary course, to use in a practical way, their statistical technique. This observation applies equally to students who have had a thorough preparation in mathematics and to those who have not. Conversation with other teachers has led me to conclude that the failure of elementary instruction to enable the student to apply his knowledge is confined to no one course or institution. This is not intended to be critical of such courses. It is probably impossible in the brief time allotted to them to develop in the student both a knowledge of statistical technique and skill in the application of method to concrete problems. The emphasis in an elementary course must be on the nature and calculation of statistical constants, rather than on argument from those constants. The emphasis must be on statistical description rather than on statistical inference. But if the study of statistical method in training for business is to be justified, it must be carried to the point where the student will have more than a bowing acquaintance with method and will acquire facility in drawing conclusions from quantitative data. It is easy to suggest this and somewhat difficult to accomplish it. The faculty which needs to be developed in the student is something in the nature of a power to see analogies between a new situation and a previous experience. The mental processes involved are perhaps obscure, and no final answer possible as to the method by which this power can be developed. But certain conditions essential to its development can be pointed out. The most important of these conditions is that the original experience of the student must be vivid. Tell the student that when the relationship between associated variables is disturbed by many minor causes, a process of curve fitting or graduation is an appropriate method for describing the normal relationship between the variables. He would promptly forget it. Give him a concrete problem involving the same principle and he will remember provided that the illustration is a significant one. The original experience of the student will be vivid in proportion as it seems to the student to have a significant conclusion. At the present time, it is

n/a

A FULL explanation of the data and methods used A1 in constructing our index of general business conditions was given in THE REVIEW OF ECONOMIC STATISTICS for January and April i919. That explanation should be consulted by readers of the REViEw who want information concerning the technique or details of the construction of the index. The majority of readers, however, are interested in results rather than in methods or technical details. The explanation which follows is designed to meet the needs of such readers. Although the explanation is non-technical, it is nevertheless complete and it is intended to give a statement sufficient for an understanding of our index. Our index of general business conditions is derived from those series of monthly items of the industrial, commercial, and financial statistics which ordinarily serve as the basis for judgments concerning the fundamental speculative, business, and banking situation. Measurement of business activity, however, is relative to some standard. Isolated items of statistical series, upon which such a measure must be based, can have no significance by themselves. Only by a comparison of items over a period of time can we ascertain their meaning. Items pertaining to widely separated periods cannot, however, be used in their crude form. Each monthly item of bank clearings, pig-iron production, interest rates, and the like, is a composite, the make-up of which depends on the year and season. That is, various elements contribute to make bank clearings for January I920, for instance, the precise total reported. In general the actual items result from the combination of four elements -secular trend, seasonal variation, cyclical fluctuation, and a residual factor. The secular trend is the regular increase or decrease, according to some principle, over the whole period under consideration. For most series it is a growth element, dependent upon population and the development of industry. There is a normal change year after year in a developing or altering industrial society, just as there is a normal change in the physical or mental status of a growing child. As used in this exposition, the expression " secular trend " may refer either to a statistical series or to one item of a series. When it refers to a series it means the straight line fitted to the data; the measure of growth is given by the slope of the straight line. When the expression refers to one item of a series it designates the vertical distance (or its numerical value) from the curve or line of trend to the zero base line. The seasonal variation is the movement of the items within the year, which we attribute to the round of the seasons. There is a seasonal change in various lines of business activity just as there is a seasonal change in temperature or rainfall. Although an iron-clad system is not to be expected, the movement of the items, to be seasonal, must be systematic year after year. The seasonal variation of an item for any month is given by an index which expresses the " normal " for that month as a percentage of the monthly average for the year. The cycles are the undulating curves, or numerical values, secured by removing from the actual items the secular trend and the seasonal variation, and expressing the results in terms of comparable units.' The actual figures thus corrected and expressed measure the rhythmic movement of business, the ebb and flow corresponding to depression and prosperity. The residual element includes all sporadic developments which affect individual series, or widespread changes due to momentous occurrences, such as wars or national catastrophes, which affect a number of series simultaneously. Thus pig-iron production may take a sudden slump if a strike occurs, railway gross earnings may drop because of unusual storms or floods; trading on the stock exchange may be greatly affected by a court decision. The continuity of nearly all series was interrupted by the outbreak of the Great War. This irregular or residual element has not been eliminated by our process of correcting the data and hence it is present, along with the cyclical fluctuation, in the statistics used in constructing our Index. In order to adapt the statistical data to our purpose, the securing of a numerical measure of the ebb and flow of business, two problems were solved; first, we devised a method of correcting the statistics for secular trend and seasonal fluctuations; that is, we unraveled the tangle of elements which constitute the fluctuations in fundamental series. In other words, we devised a method whereby the actual series of business statistics now published in our trade and financial journals were set forth in such a form as to be significant and reliable indices of business conditions. Second, having corrected the various series of fundamental statistics for secular trend and seasonal variation, it was necessary to solve another statistical problem. The corrected series have wave movements; for all corrected series the elapsed periods from crest to crest or trough to trough are approximately the same. The times, however, at which crests or troughs of the waves of the several series occur are frequently not the same. Never