A two-stage procedure on comparing several experimental treatments and a control—the common and unknown variance case

This paper introduces a two-stage selection rule to compare several experimental treatments with a control when the variances are common and unknown. The selection rule integrates the indifference zone approach and the subset selection approach in multiple-decision theory. Two mutually exclusive subsets of the parameter space are defined, one is called the preference zone (PZ) and the other, the indifference zone (IZ). The best experimental treatment is defined to be the experimental treatment with the largest population mean. The selection procedure opts to select only the experimental treatment which corresponds to the largest sample mean when the parameters are in the PZ, and selects a subset of the experimental treatments and the control when the parameters fall in the IZ. The concept of a correct decision is defined differently in these two zones. A correct decision in the preference zone (CD1) is defined to be the event that the best experimental treatment is selected. In the indifference zone, a selection is called correct (CD2) if the selected subset contains the best experimental treatment. Theoretical results on the lower bounds for P(CD1) in PZ and P(CD2) in IZ are developed. A table is computed for the implementation of the selection procedure.

An integrated selection formulation for the best normal mean: the unequal and unknown variance case

This paper considers an integrated formulation in selecting the best normal mean in the case of unequal and unknown variances. The formulation separates the parameter space into two disjoint parts, the preference zone (PZ) and the indifference zone (IZ). In the PZ we insist on selecting the best for a correct selection (CS1) but in the IZ we define any selected subset to be correct (CS2) if it contains the best population. We find the least favorable configuration (LFC) and the worst configuration (WC) respectively in PZ and IZ. We derive formulas for P(CS1|LFC), P(CS2|WC) and the bounds for the expected sample size E(N). We also give tables for the procedure parameters to implement the proposed procedure. An example is given to illustrate how to apply the procedure and how to use the table.

Effect of Turbidity on the Temporal and Spatial Utilization of the Inner Bay of Fundy by American Shad (Alosa sapidissima) (Pisces: Clupeidae) and its Relationship to Local Fisheries

Since 1750, a unique, directed fishery for American shad (Alosa sapidissima) has existed in shallow, turbid, mega-tidal embayments of the inner Bay of Fundy during summer and fall. Tagging experiments indicated that migrating shad consisting of intermixed, river populations from the entire Atlantic coast of North America occur there between June and October. Shad migration was counterclockwise around the Bay following the residual current structure. Presence and duration of the shad run in Cumberland Basin was a result of interaction between migration timing, turbidity, and temperature. Mean daytime swimming depth was related to tidal phase and turbidity. High turbidity (Secchi [Formula: see text]) of the mega-tidal embayments apparently extends the preference zone for light intensity of ocean-feeding shad into surface waters (2–10 m), making them accessible to the local fishery.Key words: drift gillnets, shad migration, light intensity preference, swimming depth, mega-tidal, eastern Canada

Graphical Model of Thermoregulatory Behavior by Fishes with a New Measure of Eurythermality

The behavioral responses of fishes, specifically preference and avoidance reactions, to temperature are described using a general graphical model based on a broad overview of the literature. A quantitative measure of eurythermality, based on the area of the thermal preference zone, is presented which offers a more meaningful estimate of the optimal thermal requirements of the species than one based on lethality alone. We also emphasize the importance of considering the preference–avoidance responses of fishes when setting ambient water quality criteria for temperature or when estimating the potential environmental impact resulting from changes in the thermal regime of an aquatic system.Key words: thermoregulation, behavior, temperature, eurythermality, thermal preference, avoidance