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Download full textSchochet, Peter Z. – National Center for Education Evaluation and Regional Assistance, 2009
This paper examines the estimation of two-stage clustered RCT designs in education research using the Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for the study population (the…
Descriptors: Control Groups, Causal Models, Statistical Significance, Computation
Peer reviewedLogan, S. R. – Journal of Chemical Education, 1995
Discusses the use of the least-squares regression line in determining the optimum straight line in an efficient and objective manner and the validity of its underlying assumptions in certain situations. Discusses the treatment of kinetic data, distortion from large errors, and the Guggenheim method. (JRH)
Descriptors: Chemistry, Data Analysis, Error of Measurement, Higher Education
Peer reviewedEdwards, Martin H. – Physics Teacher, 1989
Discusses the use of linear regression methods to extrapolate experimental data. Describes the method of averages and two weighted least squares. Calculates the error range of each method. (YP)
Descriptors: College Science, Error of Measurement, Least Squares Statistics, Physics
Peer reviewedDeacon, Christopher G. – Physics Teacher, 1992
Describes two simple methods of error analysis: (1) combining errors in the measured quantities; and (2) calculating the error or uncertainty in the slope of a straight-line graph. Discusses significance of the error in the comparison of experimental results with some known value. (MDH)
Descriptors: Error of Measurement, Goodness of Fit, High Schools, Higher Education
