The relationship between the principals\u27 preferred leadership styles and levels of implementation of character education programs in Kanawha County Schools.

This study was conducted to determine if there was a relationship between the independent variable, leadership styles of Kanawha County Schools (KCS) principals, and the dependent variable of implementation levels of character education programs. The population of the study included all principals in KCS (n = 87). The sample used for the study also included all principals in KCS (n = 87). The instruments used for collection of data in the study included: (a) Leadership Behavior Description Questionnaire-Self (LBDQ-Self), (b) Character Education Assessment Checklist (CEAC), and (c) Demographic Survey of KCS Principals. The instruments were completed by the respondents in the October\u27s Principal\u27s meeting. The respondents were encouraged to complete the instruments in an open and honest manner and anonymity was insured for the respondent and their school. The Statistical Product & Service Solutions (SPSS) package was used to analyze the data collected. A linear regression, t-test, frequency distributions and a Scheffe\u27s post hoc analysis were used to determine relationships. The results of the t-test indicated that there was no significant relationships. However, the linear regression indicated there was a significant relationship. The linear regression indicated that as the principals initiating structure score increased, as measured by the LBDQ-Self, there were significantly higher levels of implementation of character education. The Scheffe\u27s Post Hoc Analyses indicated a significance at the elementary and middle school levels when compared to the 9–12 high schools. The principals with initiating structure identified as their leadership style, as measured by the LBDQ-Self, had significantly higher levels of implementation of character education programs than the principals of the 9–12 high schools

The influence of selected economic and social factors on meat consumption

This study was designed: (1) to develop consumption functions for total meat, beef, pork, poultry, cold cuts, and fish and seafood using selected economic and social factors of households in five income groups ($0-2,999,$3,000-5,999, $6,000-8,999,$9,000-11,999, and $12,000 and over), (2) to compare mean quantities purchased and expenditures for each kind of meat for the five income groups, and (3) to estimate income elasticities and consumer unit elasticities for each of the five income groups. Data were obtained in Knox County, Tennessee, from 215 families for a ten week period beginning September 4 and ending November 12, 1967. Least squares regression was used to fit three linear models to the meat consumption data within the five income groups for each kind of meat. Model I designated quantities purchased or expenditures for meat to be a function of annual disposable household income. Model II denoted the dependent variable, quantities purchased or expenditures, to be a function of annual disposable household income and consumer units. Model III postulated the quantities purchased or expenditures for meat to be a function of annual disposable household income, consumer units, race, number of people receiving an income per household, number of social groups the homemaker belongs to, age of the head of the household, who does the food purchasing, religion, occupation, number of meals served to guests, number of meals eaten by children at school, number of meals eaten out, education of the homemaker, and education of the husband. Dummy variables were used to represent the variables that are not usually measured on a numerical scale. Within most income groups the variation in income explained little of the variation in the quantities purchased and expenditures for meat. But, consumer units, in general, explained a large percentage of the variation in the consumption of total meat, beef, pork, and cold cuts. Neither income nor consumer units explained much of the variation in quantities purchased or expenditures for poultry or fish and seafood. The other social and economic variables were significant for certain income group-kind of meat combinations. However, no variable was consistently significant for all income group-kind of meat combinations. A comparison of the income elasticities computed from the models indicated that the magnitude and signs of income elasticities varied considerably between models and between income groups. The magnitude of income elasticities computed from significant coefficients for the same income group and the same kind of meat, but for different models, varied as much as 75 percent indicating that the magnitude of income elasticity was influenced by the presence of other variables in the regression equation. In general, consumer unit elasticities for both quantities purchased and expenditures for total meat, beef, pork, and fish and seafood were less than one. Most of the consumer unit elasticities for both quantities purchased and expenditures for cold cuts were greater than one indicating that cold cuts were more responsive to changes in consumer units than total meat, beef, pork, or fish and seafood. More research is needed regarding how income elasticity changes with the level of income. The results of this study indicate that the common practice of discussing income elasticity in singular terms is often not appropriate. Also, income elasticities vary considerably as the number of variables in the equation changes. More research is needed regarding when and by how much elasticities are influenced by other variables

Using GIS to Model the Timbershed of a Wood Based Manufacturing Facility

A geographic information system (GIS) is an excellent tool for determining timber procurement zones. This study focuses on the procurement zones of two wood processing facilities in Arkansas, one in Fort Smith and one near Menifee. Since the two mills began operation in 1995, there have been questions about the long-term effect on the hardwood timber resource of the region. The wood basket for these mills must first be determined before their effects can be studied. Transportation from the harvest site to the primary processing facility accounts for a large portion of the total mill-delivered cost for raw material and this cost limits the range that raw woody material can be shipped. Determining transportation costs using GIS and U.S Census Bureau topographically integrated geographic encoding and reference (TIGER) line files of existing road systems can aid managers in determining procurement zones. Spatial analysis was conducted using the GIS software ArcView 3.1 (ESR Redlands, CA). The ArcView Spatial Analyst extension was used to divide the study area into 30 x 30 meter cells, and the each cell was queried to determine which of the predetermined road classes exists and a cost per cell was assigned. Total transportation costs were then determined based on road class. The result is a travel cost surface that more accurately predicts transportation costs than the traditional concentric cost rings extending from a mill in specified intervals

Electronic Data Transmission Pathways: Implications for Site Selection

Current technology and cost of on-site data transmission hardware, site communications channels, and interface equipment allow a firm the capability to routinely achieve both high speed and high quality of data transmission. However, the firm can easily exceed the capability of a common carrier's local and regional pathways (lines and switch gear), resulting in reduced cost effectiveness of business operations. This study presents a telecommunications evaluation structure that can be integrated into the firm's site selection and facilities planning decision framework. This structure is used to assess the capability of sites to meet required telecommunications support. Additional considerations affecting data transmission capability are included to assist the analyst in the evaluation progress.

Evaluating the most promising sites for wind energy development in Arizona USA: Working paper series--05-09

During the summer of 2003, the state of Arizona took delivery of a set of high-resolution wind energy maps. After applying various exclusions, the developable wind energy potential is 23,290 MW of class 3 or higher, 2,630 MW of class 4 or higher, and 775 MW of class 5 or higher winds. Having determined the potential wind resource, the geographical information system data supplied with the wind maps was used to create a wind resource inventory and to systematically identify the most promising sites for wind energy development. In addition to wind energy potential, proximity to transmission lines and roads, and land ownership were considered in this analysis. Following that, the cost of energy was estimated at a few geographically diverse sites, including class 3, 4, and 5 wind resource areas, at a hub height of 70 m. These estimates revealed that the real levelized cost of energy in 2005 dollars ranged from 4.21 to 5.04 cents per kWh, as the wind class varies from 5 to 3. This paper documents the findings of the wind mapping process, describes the method and results of evaluating the most promising sites for wind development, and presents the cost of energy results

New Method for Evaluating Activities in Ternary Nonaqueous Solutions Through Infrared Spectroscopy

Inorganic Chemistr

Economic Analysis of Selected Technological Developments in Cotton Production

Agricultural Economic

Action and Interaction of Physiological Food Intake Regulators in the Laying Hen

Animal Nutritio

Some geographic and economic aspects of building a superhighway from Chicago to East Saint Louis

Thesis (M.S.)--University of Illinois at Urbana-Champaign, 1950.Includes bibliographical references