Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- A/B testing (1)
- Ausubel's Theory of Meaningful Learning (1)
- College (1)
- Conditional auto-regressive model (1)
- D-optimal design (1)
-
- Demographics (1)
- Ebbinghaus's Spacing Effect Theory and Forgetting Curve (1)
- Envelope (1)
- FBO (1)
- Flight Time to Proficiency (1)
- Local Modal MAVE (1)
- Mixed integer programming (1)
- Part 141 (1)
- Part 61 (1)
- Private Pilot Check Ride (1)
- Re-randomization (1)
- Robust Estimation (1)
- Shrinkage Estimation (1)
- Social network (1)
- Spatial Process (1)
- Sufficient Dimension Reduction (1)
- Training Time to Proficiency (1)
- Variable Selection. (1)
Articles 1 - 3 of 3
Full-Text Articles in Statistics and Probability
The Private Pilot Check Ride: Applying The Spacing Effect Theory To Predict Time To Proficiency For The Practical Test, Michael Scott Harwin
The Private Pilot Check Ride: Applying The Spacing Effect Theory To Predict Time To Proficiency For The Practical Test, Michael Scott Harwin
Theses and Dissertations
This study examined the relationship between a set of targeted factors and the total flight time students needed to become ready to take the private pilot check ride. The study was grounded in Ebbinghaus’s (1885/1913/2013) forgetting curve theory and spacing effect, and Ausubel’s (1963) theory of meaningful learning. The research factors included (a) training time to proficiency, which represented the number of training days needed to become check-ride ready; (b) flight training program (Part 61 vs. Part 141); (c) organization offering the training program (2- or 4-year college/university vs. FBO); (d) scheduling policy (mandated vs. student-driven); and demographical variables, which …
Statistical Designs For Network A/B Testing, Victoria V. Pokhilko
Statistical Designs For Network A/B Testing, Victoria V. Pokhilko
Theses and Dissertations
A/B testing refers to the statistical procedure of experimental design and analysis to compare two treatments, A and B, applied to different testing subjects. It is widely used by technology companies such as Facebook, LinkedIn, and Netflix, to compare different algorithms, web-designs, and other online products and services. The subjects participating in these online A/B testing experiments are users who are connected in different scales of social networks. Two connected subjects are similar in terms of their social behaviors, education and financial background, and other demographic aspects. Hence, it is only natural to assume that their reactions to online products …
Dimension Reduction And Variable Selection, Hossein Moradi Rekabdarkolaee
Dimension Reduction And Variable Selection, Hossein Moradi Rekabdarkolaee
Theses and Dissertations
High-dimensional data are becoming increasingly available as data collection technology advances. Over the last decade, significant developments have been taking place in high-dimensional data analysis, driven primarily by a wide range of applications in many fields such as genomics, signal processing, and environmental studies. Statistical techniques such as dimension reduction and variable selection play important roles in high dimensional data analysis. Sufficient dimension reduction provides a way to find the reduced space of the original space without a parametric model. This method has been widely applied in many scientific fields such as genetics, brain imaging analysis, econometrics, environmental sciences, etc. …