Suchergebnisse

Solutions to common problems in preelection surveys are described using the Gallup Poll as an example. A history of sampling theory is given, & examined are problems in & solutions to: (1) sampling, (2) estimation, (3) response validity, (4) the undecided, (5) measuring the likelihood to vote, & (6) measuring late trends in voter preference. Cited are demonstrable gains in accuracy that have followed application of the described solutions. 1 Table. Modified HA.

This paper presents the first draft of a chapter on the survey methodology which is intended to be part of a larger report on the Mbere study. It presents a straightforward summary firstly of the objectives of the survey and the reasons for their selection and secondly of the methods which were employed to collect the data

Survey methodology in 1948 was practically unknown and by 1953 due to the influence of the Reactions Analysis Staff of the US High Commissioner in Germany has been growing to a point where a number of institutes such as Institute fuer Sozialforschung (Frankfurt/Main), Institute fuer Demoskopie (Allensbach/Bodensee) and Institute fur Sozialwissenschaften have been organized and doing research. It is suggested that better methodology could be used by German organizations, and that a greater effort be expended into micro-economic studies to better understand German economic revival; economic attitudes, toward saving, distribution of income, and income increase and/or decrease by types of families. L. P. Chall.

The paper outlines the preparation and implementation of a land use and socio-economic survey in Loitokitok and Ngong Divisions of Kajiado District

ABSTRACTThis paper illustrates the use of the Box‐Jenkins methodology by analyzing the Ohio Electrical Power Consumption time series. The three basic analytical steps discussed are the following:1) Model identification ‐ by matching sample autocorrelation functions against theoretical autocorrelation functions.2) Non‐linear estimation of parameters ‐ by minimizing the sum of the squared residuals.3) Diagnostic checking ‐ by analyzing the pattern of the autocorrelation function of the residuals.Regular and adaptive forecasts are then developed using the appropriate model that emerges from the time series analysis.