본문

  1. Home
  4. Thesis
25 Results:SS:HYPOTHESIS 0.265 sec.
RSS 
Multilingual
 Advanced Search
 New arrival Search
Selected Print 선택엑셀내보내기
1
Frequentist and Bayesian Hypothesis Testing Focusing on Meaningful Effect Sizes.
Frequentist and Bayesian Hypothesis Testing Focusing on Meaningful Effect Sizes.
Midya, Vishal. | The Pennsylvania State University. | 2020
Print
2
Classical Nonparametric Hypothesis Tests with Applications in Social Good
Classical Nonparametric Hypothesis Tests with Applications in Social Good
Ottoboni, Kellie. | University of California, Berkeley | 2019
Print
3
Essays in Experimental Economics and Non-Bayesian Learning.
Essays in Experimental Economics and Non-Bayesian Learning.
Galindo Prieto, Jimena.Economics. | New York University. | 2024
Print
4
A Gaussian-Process Framework for Nonlinear Statistical Inference Using Modern Machine Learning Models- [electronic resource]
A Gaussian-Process Framework for Nonlinear Statistical Inference Using Modern Machine Learning Models- [electronic resource]
Deng, Wenying.Biostatistics. | Harvard University. | 2023
Print
5
Inference of Cascades and Correlated Networks- [electronic resource]
Inference of Cascades and Correlated Networks- [electronic resource]
Sridhar, Anirudh.Electrical and Computer Engineeri | Princeton University. | 2023
Print
6
Hardware-Aided Approaches for Unconditional Confidentiality and Authentication.
Hardware-Aided Approaches for Unconditional Confidentiality and Authentication.
Bendary, Ahmed.Electrical and Computer Engineering | The Ohio State University. | 2021
Print
7
Essays on the Efficiency of Tests in Econometrics.
Essays on the Efficiency of Tests in Econometrics.
Engle, Samuel P.Economics. | The University of Wisconsin - Madison. | 2022
Print
8
Dry Runs and "PWRD" Aggregation: Two New Methods for Extracting Power from Careful Observation of a Randomized Controlled Trial's Context.
Dry Runs and "PWRD" Aggregation: Two New Methods for Extracting Power from Careful Observation of a Randomized Controlled Trial's Context.
Lycurgus, Timothy P.Statistics. | University of Michigan. | 2022
Print
9
Statistical Learning for Latent Attribute Models.
Statistical Learning for Latent Attribute Models.
Ma, Chenchen.Statistics. | University of Michigan. | 2022
Print
10
Testing for a Difference in Means After Selection.
Testing for a Difference in Means After Selection.
Chen, Yiqun.Biostatistics - Public Health. | University of Washington. | 2022
Print
처음123이후마지막