A computer program to find the best-fitting orthogonal factors for a given hypothesis

A modification of the quartimax computation for factor rotation is described in which a hypothesized factor pattern is given to the machine along with the data. The machine uses the pattern to select the subset of variables to which it will attend when rotating in a given plane, in order to find an orthogonal solution which closely fits the hypothesis. The program also provides a measure of the goodness of this fit. The program can utilize pattern matrices that reflect only partial hypotheses as to the nature of the factors, as well as those that specify highly determined simple structure.     

Evidence

Conclusion We can now see, perhaps, what merits if any this definition has. It ties in the concept of evidence with that of law, and requires us to support our claim that some fact (or statement) is evidence for another by pointing out the science, and within it the law (or what meets the tests of being acceptable as such) whose existence alone justifies us in assuming that a certain conditional statement qualifies as acceptable as nomological. Whoever claims that a certain fact is evidence for another is required to justify his assumption that there exists a certain law. That in some sense there are such justifiable assumptions is clear from the existence of natural sciences and technologies based upon them. But it will turn out that in many cases it is impossible, as of a given moment, to make out a case for the claim that a certain conditional statement, required to support the view that a certain fact is evidence for another, is nomological. In such cases we are able to draw a clear line between what someone may think or claim is evidence, and what we have reasonable grounds for accepting as such. In short the concept offers us a principle of demarcation between justified and unjustified claims for the evidential nature of facts (or statements) offered as such. If this is not a very impressive achievement still it is not wholly contemptible, considering the confusion that prevails among many people concerning the question of evidence.     

Characteristics of Counseling Centers in Large Universities

Factual and subjective data gathered from counseling centers in 36 major universities is presented to show present conditions, emphasis, and needs of the future. Data are presented showing ratios of counselors to students, budget allotments, strengths, specific weaknesses, etc. Counseling facilities, services provided, emphasis, communications and plans for expansion are dealt with individually. Less than half the centers were meeting student needs and a majority indicated a shortage of professional staff, particularly those competent to do personal adjustment counseling.     

Dyadic decisions with numerical and verbal probabilities

The goal of the research was to compare decisions under risk in a situation in which forecasters (F) communicate to decision makers (DM) either numerically (e.g., .70) or verbally (e.g., likely) about the chances that a binary event will occur. Following each forecast, the DM bid for a winning or losing lottery based on the event. In Experiment 1 Fs and DMs also provided numerical translations of each verbal forecast after the DMs' bid. In Experiment 2 the DMs provided membership functions over the [0, 1] interval for each phrase used by the Fs. The primary results were: (a) extreme similarity in the DM's bids and rates of bidding under the two modes of communication; (b) greater variability in bids to specific verbal than numerical forecasts; (c) a pattern of bids, in which DMs demonstrated risk seeking for gains and risk neutrality for losses; (d) DMs' numerical translations in Experiment 1 were closer to .50 than were those of Fs; and (e) phrases selected by Fs had high membership values to DMs for the probabilities the Fs were attempting to describe. Points (a), (b), (d), and (e) are consistent with the ν-μ model which assumes that the vague meaning of a probability phrase can be represented by a membership function over the [0, 1] interval, and that in reaching a decision the DM focuses on a range of probabilities with sufficiently high membership. Point (c) is speculatively attributed to social aspects of the dyadic situation, and requires further investigation.