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) | 1 |
Descriptor
Data Analysis | 4 |
Data Interpretation | 4 |
Statistical Significance | 4 |
Effect Size | 2 |
Probability | 2 |
Research Methodology | 2 |
Sample Size | 2 |
Sampling | 2 |
Statistical Analysis | 2 |
Statistics | 2 |
Case Studies | 1 |
More ▼ |
Author
Barbella, Peter | 1 |
Hitch, Graham J. | 1 |
Jillian Haut | 1 |
Maryellen Brunson McClain | 1 |
Rochelle B. Schatz | 1 |
Thompson, Bruce | 1 |
Tiffany L. Otero | 1 |
Towse, John N. | 1 |
Publication Type
Reports - Descriptive | 3 |
Books | 1 |
ERIC Digests in Full Text | 1 |
ERIC Publications | 1 |
Journal Articles | 1 |
Non-Print Media | 1 |
Education Level
Audience
Practitioners | 1 |
Teachers | 1 |
Location
United Kingdom (Great Britain) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Maryellen Brunson McClain; Tiffany L. Otero; Jillian Haut; Rochelle B. Schatz – Sage Research Methods Cases, 2014
With growing popularity of single subject design as a method to evaluate the efficacy of interventions, it is important to ensure that the analyses of these methods are rigorous and reliable. The purpose of this case study is to discuss the measures used to evaluate the efficacy of interventions in single subject design studies in the fields of…
Descriptors: Educational Research, Effect Size, Data Analysis, Data Interpretation

Towse, John N.; Hitch, Graham J. – 1994
This paper summarizes an experiment conducted to examine the counting performance of 7- and 8-year-olds. Analysis of variance was computed on counting errors produced when enumerating a set of squares on a computer screen. The factors included in the analysis were age, gender, array size, error type, proximity, and error form. The primary…
Descriptors: Computation, Data Analysis, Data Interpretation, Error Patterns

Barbella, Peter; And Others – Mathematics Teacher, 1990
Demonstrates a statistically valid method allowing students to explore randomization. Described are two examples: counting techniques for a small set of data and simulation for a large sample. (YP)
Descriptors: Data Analysis, Data Interpretation, Mathematical Concepts, Mathematical Logic
Thompson, Bruce – 1994
Too few researchers understand what statistical significance testing does and does not do, and consequently their results are misinterpreted. This Digest explains the concept of statistical significance testing and discusses the meaning of probabilities, the concept of statistical significance, arguments against significance testing,…
Descriptors: Data Analysis, Data Interpretation, Decision Making, Effect Size