Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 0 |
Since 2006 (last 20 years) | 2 |
Descriptor
Publication Type
Numerical/Quantitative Data | 4 |
Reports - Descriptive | 4 |
Reports -… | 1 |
Education Level
High Schools | 2 |
Secondary Education | 2 |
Grade 9 | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Audience
Location
New York (New York) | 1 |
Texas | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kemple, James J. – Research Alliance for New York City Schools, 2015
In the first decade of the 21st century, the New York City (NYC) Department of Education implemented a set of large-scale and much debated high school reforms, which included closing large, low-performing schools, opening new small schools, and extending high school choice to students throughout the district. The school closure process was the…
Descriptors: High Schools, School Closing, Academic Achievement, Outcomes of Education
Johnson, Roy L.; Montes, Felix – Intercultural Development Research Association, 2012
This document contains 3 statistical reports. The first report, "Attrition Rate Decline Seems Promising--Though High Schools are Still Losing One in Four Students" (by Roy L. Johnson), presents results of long-term trend assessments of attrition data in Texas public high schools. The second report, "Slow Declining Pace Keeps Zero…
Descriptors: High School Students, Trend Analysis, Educational Trends, Prediction
van Engelenburg, Gijsbert – 1999
The Solomon four-group design (R. Solomon, 1949) is a very useful experimental design to investigate the main effect of a pretest and the interaction of pretest and treatment. Although the design was proposed half a century ago, no proper data analysis techniques have been available. This paper describes how data from the Solomon four-group design…
Descriptors: Foreign Countries, Maximum Likelihood Statistics, Outcomes of Treatment, Pretests Posttests
Blankmeyer, Eric – 1993
Ordinary least-squares regression treats the variables asymmetrically, designating a dependent variable and one or more independent variables. When it is not obvious how to make this distinction, a researcher may prefer to use orthogonal regression, which treats the variables symmetrically. However, the usual procedure for orthogonal regression is…
Descriptors: Equations (Mathematics), Estimation (Mathematics), Least Squares Statistics, Mathematical Models