J-This paper is based upon a dissertation submitted to the Graduate School of the University of Colorado in partial fulfillment of the requirements for the PhD degree. The research was in part performed while the writer held a predoctoral fellowship from the National Institute of Mental Health. The writer wishes to thank K. E. Davis and D. Mason for their advice and assistance, and is especially indebted to F. J. Todd, his dissertation chairman.8 Now at the University of Denver.

Most Ss in probability-learning experiments do not maximize, perhaps because they expect sequential patterns. The purpose of this experiment was to determine whether or not the elimination of the objective tenability of sequential dependencies would increase the proportion of maximizing responses. 21 Ss in the experimental condition controlled the random generation of events by the throw of a die so that sequential dependencies were objectively unreasonable. 21 control Ss were presented prearranged sequences, making it reasonable for S to anticipate sequential patterns. Results confirmed the experimental hypothesis ; experimental conditions led to more maximizing responses than did control conditions at the .01 level of significance.

3 experiments evaluated the degree to which relations within sets of subjective probabilities conformed to implications of mathematical probability theory. According to probability theory, 2 products of subjective probabilities, ^(a)^(b|a) and ^(b)^(a|b), should be equal. The mean correlation between these products was .67 in Experiment I. The corresponding correlation was .90 in Experiment II after partialing out the effect of relevant objective probabilities. In Experiment III, Ss made trial-to-trial revisions of subjective probabilities which referred to 2 classes of events. Although the magnitude of subjective-probability revision was less than the magnitude of objective-probability revision, the relation between revised subjective probabilities associated with the 2 classes of events agreed closely with the relation specified by probability theory.Two important characteristics of subjective probabilities can be distinguished-veridicality and consistency. The subjective probability of X, \i/(X), is veridical to the extent that its value agrees with the corresponding objective probability, P(X).

Initially, wilderness users suggested about 30 types of rewards they felt they gained from wilderness experience. Importance ratings suggesting the value of these rewards were obtained from a sample of college students. Individual rewards rated most important were tranquility, natural beauty, and escape from the hectic urban pace. Factoring the importance ratings of the 30 reward items yielded five categories of rewards gained in wilderness which were somewhat similar to those found in previous research: emotional or spiritual experience, challenge and adventure, esthetic enjoyment of natural settings, escape from urban stresses, and, perhaps, an antisocietal sentiment. These college students also indicated their expectations for achieving the 30 rewards in five different leisure environments including wildemess. In general, expectations decreased progressively from wildemess, through improved mountain-forest country, parks and other urban outdoor settings, to indoor recreational settings and home. The implications of this pattern were discussed in terms of a potentially diminished opportunity structure if wilderness land becomes unavailable for public use, possibly resulting in socially undesirable Alternative means for gaining rewards.

2The integration of information model ofsignal detection theory (SDT) was tested in a multiple observation tilt-discrimination task. Improvement in discriminability with additional observations was consonant with theory over two observations, but observations beyond the second yielded less improvement than predicted by the integration model. Analyses of operating characteristics lent some support to the applicability of SDr to the tilt-discrimination task.This paper describes two experiments designed to test the integration model of signal detection theory (SOT) in a multiple observation task (cf. Green & Swets, 1966). In opposition to traditional threshold theory which posits an all-or-nothing informing effect of stimuli, SOT states that the informing effects range along a continuum from determinate information favoring one stimulus alternative through no information to determinate information favoring the other alternative. A stimulus is evaluated by comparing its informing effect with an internal standard or criterion. The probability density function of the informing effects yielded by a given stimulus source is assumed to be normal. In a two-alternative discrimination task, the informing effects density functions associated with the alternative stimuli would differ in location, but, for the sake of simplicity, can be assumed to be equal in variance. The difference between the means of the probability density functions, in units of the density function standard deviation, is labeled the index of signal detectability (d') and constitutes the SOT measure of discriminability-sensitivity.In order to derive predictions of discriminability when multiple observations of the stimulus are furnished on each trial, it is assumed that the informing effect associated with a set of independent observations is the mean of the informing effects of the component observations. Thus, the probability density function for a set of n observations should possess the same location on the informing effects continuum as the density function for single observations. However, the standard deviation should be only If./ii (n being the number of observations) of the standard deviation of the single observation density function. Because d' is the ratio of the difference in location to the standard deviation of the density functions, reduction in the standard deviation yields a proportional increase in d'. Thus, the d' based on n observations per trial is predicted by the SOT integration model to be v'n times the d' based on one observation per trial. The v'nprediction requires the assumption that the multiple stimulus observations are mutually independent. If dependence should exist, the predicted improvement would be less than v'n. It may be noted that the same predictions can be derived if one assumes that S bases his judgment on the likelihood ratio of the informing effects, and that the likelihood ratio of a set of stimulus observations is the product of the likelihood ratios of the individual observations (Green & Swets, 1966).In an a...