Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Credibility | 2 |
| Statistical Analysis | 2 |
| Statistical Inference | 2 |
| Beliefs | 1 |
| College Faculty | 1 |
| Computation | 1 |
| Correlation | 1 |
| Data | 1 |
| Least Squares Statistics | 1 |
| Multiple Regression Analysis | 1 |
| Sampling | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 2 |
| Opinion Papers | 1 |
| Reports - Evaluative | 1 |
| Reports - Research | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkSchouten, Rianne Margaretha; Vink, Gerko – Sociological Methods & Research, 2021
Missing data in scientific research go hand in hand with assumptions about the nature of the missingness. When dealing with missing values, a set of beliefs has to be formulated about the extent to which the observed data may also hold for the missing parts of the data. It is vital that the validity of these missingness assumptions is verified,…
Descriptors: Data, Validity, Beliefs, Statistical Analysis
Download full textOsborne, Jason W. – Practical Assessment, Research & Evaluation, 2013
Osborne and Waters (2002) focused on checking some of the assumptions of multiple linear regression. In a critique of that paper, Williams, Grajales, and Kurkiewicz correctly clarify that regression models estimated using ordinary least squares require the assumption of normally distributed errors, but not the assumption of normally distributed…
Descriptors: Multiple Regression Analysis, Least Squares Statistics, Computation, Statistical Analysis
