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Shashi Bhushan; Anoop Kumar – Measurement: Interdisciplinary Research and Perspectives, 2024
The data we encounter in real life often contain missing values. In sampling methods, missing value imputation is done with different methods. This article proposes novel logarithmic type imputation methods for estimating the population mean in the presence of missing data under ranked set sampling (RSS). According to the determined theoretical…
Descriptors: Research Problems, Sampling, Computation, Mathematical Formulas
Bolondi, Giorgio; Ferretti, Federica; Maffia, Andrea – Teaching Mathematics and Its Applications, 2020
The process of pairing a name with representations or peculiar properties permeates many mathematics classroom situations. In school, many practices go under the label 'definition', even though they can be very different from what mathematicians conceive as a formal definition, and in fact there are substantial differences between these different…
Descriptors: Algebra, Mathematical Formulas, Definitions, High Schools
Deke, John; Wei, Thomas; Kautz, Tim – National Center for Education Evaluation and Regional Assistance, 2017
Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…
Descriptors: Intervention, Educational Research, Research Problems, Statistical Bias
Rhodes, William – Evaluation Review, 2012
Research synthesis of evaluation findings is a multistep process. An investigator identifies a research question, acquires the relevant literature, codes findings from that literature, and analyzes the coded data to estimate the average treatment effect and its distribution in a population of interest. The process of estimating the average…
Descriptors: Social Sciences, Regression (Statistics), Meta Analysis, Models
Peer reviewedAiken, Lewis R. – Educational and Psychological Measurement, 1981
This paper presents formulas that can be used to approach the problem of nonresponse in survey research. (Author/AL)
Descriptors: Mathematical Formulas, Research Problems, Surveys
Robertson, William C. – Science and Children, 2007
Using "error bars" on graphs is a good way to help students see that, within the inherent uncertainty of the measurements due to the instruments used for measurement, the data points do, in fact, lie along the line that represents the linear relationship. In this article, the author explains why connecting the dots on graphs of collected data is…
Descriptors: Graphs, Mathematical Formulas, Error of Measurement, Measurement
Peer reviewedCallender, John C.; Osburn, H. G. – Journal of Educational Measurement, 1979
Some procedures for estimating internal consistency reliability may be superior mathematically to the more commonly used methods such as Coefficient Alpha. One problem is computational difficulty; the other is the possibility of overestimation due to capitalization on chance. (Author/CTM)
Descriptors: Higher Education, Mathematical Formulas, Research Problems, Sampling
Peer reviewedHumphreys, Lloyd G. – Journal of Educational Psychology, 1980
Many researchers, including Buriel (EJ 187 987), incorrectly compared the results in each study with null hypotheses of zero differences between means or zero population correlations. Instead, a test of difference between the mean differences in the two samples or the direct comparison of the two sample correlations is required. (Author/CP)
Descriptors: Comparative Analysis, Correlation, Hypothesis Testing, Mathematical Formulas
Peer reviewedGross, Alan L. – Educational and Psychological Measurement, 1982
It is generally believed that the correction formula will yield exact correlational values only when the regression of z on x is both linear and homoscedastic. The formula is shown to hold for nonlinear heteroscedastic relationships. A simple sufficient condition for formula validity and estimation predictions is demonstrated in a numerical…
Descriptors: Correlation, Data Analysis, Mathematical Formulas, Predictor Variables
Peer reviewedStavig, Gordon R. – Perceptual and Motor Skills, 1982
The normalized mean is developed and discussed as a descriptive measure of central location. The advantages of the normalized mean over the arithmetic mean, median, and trimmed mean are discussed. (Author)
Descriptors: Mathematical Formulas, Research Problems, Scores, Statistical Analysis
Peer reviewedMiller, Richard B.; Wright, David W. – Journal of Marriage and the Family, 1995
Bias due to attrition of respondents poses a threat to the internal and external validity of research findings. Discusses methods of detecting attrition bias in longitudinal family research, and presents Heckman's procedure to correct attrition bias. Data from the University of California Longitudinal Study of Generations are used to illustrate…
Descriptors: Attrition (Research Studies), Data Interpretation, Higher Education, Longitudinal Studies
Delucchi, Kevin L. – 1981
The proper use of Pearson's chi-square for the analysis of contingency tables is reviewed. A 1949 article by Lewis and Burke, in which they cite nine primary sources of error in the use of chi-square, serves as the basis of the review. Those nine sources of error are re-examined in light of current research. In addition, techniques and research on…
Descriptors: Educational Research, Error of Measurement, Goodness of Fit, Literature Reviews
Peer reviewedPlomin, Robert; Daniels, Denise – Merrill-Palmer Quarterly, 1984
Discusses the concept of temperament interactions in the context of statistical interaction. Categorizes temperament interactions that involve temperament as an independent variable, as a dependent variable, or as both. Describes use of hierarchical multiple regression for the analysis of temperament interactions. (Author/CI)
Descriptors: Classification, Environmental Influences, Family Environment, Hypothesis Testing
Peer reviewedCohen, L. Jonathan – Cognition, 1979
Until recently, norms of experimental reasoning have lacked systematic theoretical development. Thus, it has been easy for psychologists like Tversky and Kahneman to misclassify certain human reasoning processes as being Pascalian and invalid, rather than as being Baconian and valid. (CP)
Descriptors: Abstract Reasoning, Cognitive Processes, Higher Education, Logical Thinking
Mercil, Steven Bray; Williams, John Delane – 1984
This study used species diversity indices developed in ecology as a measure of socioethnic diversity, and compared them to Coleman's Index of Segregation. The twelve indices were Simpson's Concentration Index ("ell"), Simpson's Index of Diversity, Hurlbert's Probability of Interspecific Encounter (PIE), Simpson's Probability of…
Descriptors: Comparative Analysis, Data Analysis, Elementary Secondary Education, Mathematical Formulas
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