Statistics

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  • Department Courses Table

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    Statistics Courses with "Statistics" in their name Table

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Statistics Statistics     bar_chart_4_bars

Department Course Count
93
Longest Course Name
The Challenge Problems Paradigm in Empirical Machine Learning and Beyond
Longest Course Name Length (chars)
72
Shortest Course Name
Sampling
Shortest Course Name Length (chars)
8
Lower Division Course Count
0, 0.0%
Upper Division Course Count
0, 0.0%
Graduate Courses Count
0, 0.0%
Average Course Name Length (characters)
32
Number of Statistics Courses with "Statistics" in their name
26, 28.0%

Statistics Department Courses Table

Statistics Stanford University
Course Name Course Code Course Hours Classification
Mathematics of Sports STATS100 idk too hard
Introduction to Statistics for Engineering and the Sciences STATS110 idk too hard
Introduction to Probability Theory STATS117 idk too hard
Probability Theory for Statistical Inference STATS118 idk too hard
Introduction to Statistics for Biology STATS141 idk too hard
Introduction to Applied Statistics STATS191 idk too hard
Introduction to R STATS195 idk too hard
Independent Study STATS199 idk too hard
Introduction to Theoretical Statistics STATS200 idk too hard
Philosophical Foundations of Statistics STATS200Q idk too hard
Statistical Learning and Data Science STATS202 idk too hard
Statistical Learning and Data Science [Flipped] STATS202F idk too hard
Regression Models and Analysis of Variance STATS203 idk too hard
Sampling STATS204 idk too hard
Introduction to Nonparametric Statistics STATS205 idk too hard
Applied Multivariate Analysis STATS206 idk too hard
Time Series Analysis STATS207 idk too hard
Resampling Methods: Bootstrap, Cross Validation and Beyond STATS208 idk too hard
Introduction to Causal Inference STATS209 idk too hard
Meta-research: Appraising Research Findings, Bias, and Meta-analysis STATS211 idk too hard
Machine Learning Theory STATS214 idk too hard
Statistical Models in Biology STATS215 idk too hard
Introduction to Stochastic Processes I STATS217 idk too hard
Introduction to Stochastic Processes II STATS218 idk too hard
Stochastic Processes STATS219 idk too hard
Machine Learning Methods for Neural Data Analysis STATS220 idk too hard
Random Processes on Graphs and Lattices STATS221 idk too hard
Sequential Analysis STATS223 idk too hard
Machine Learning STATS229 idk too hard
Machine Learning for Sequence Modeling STATS232 idk too hard
NeuroTech Training Seminar STATS242 idk too hard
Mathematical Finance STATS250 idk too hard
Causal Inference in Clinical Trials and Observational Studies STATS251 idk too hard
Workshop in Biomedical Data Science STATS260A idk too hard
Workshop in Biomedical Data Science STATS260B idk too hard
Workshop in Biomedical Data Science STATS260C idk too hard
Intermediate Biostatistics: Analysis of Discrete Data STATS261 idk too hard
Intermediate Biostatistics: Regression, Prediction, Survival Analysis STATS262 idk too hard
Design of Experiments STATS263 idk too hard
Foundations of Statistical and Scientific Inference STATS264 idk too hard
Bayesian Statistics STATS270 idk too hard
Applied Bayesian Statistics STATS271 idk too hard
Massive Computational Experiments, Painlessly STATS285 idk too hard
Computing for Data Science STATS290 idk too hard
Statistical Models of Text and Language STATS292 idk too hard
Industrial Research for Statisticians STATS298 idk too hard
Independent Study STATS299 idk too hard
Theory of Statistics I STATS300A idk too hard
Theory of Statistics II STATS300B idk too hard
Theory of Statistics III STATS300C idk too hard
Statistics Teaching Practicum STATS301 idk too hard
Qualifying Exams Workshop STATS302 idk too hard
Statistics Faculty Research Presentations STATS303 idk too hard
Applied Statistics I STATS305A idk too hard
Applied Statistics II STATS305B idk too hard
Applied Statistics III STATS305C idk too hard
Time Series Analysis STATS307 idk too hard
Theory of Probability I STATS310A idk too hard
Theory of Probability II STATS310B idk too hard
Theory of Probability III STATS310C idk too hard
Information Theory and Statistics STATS311 idk too hard
Advanced Statistical Theory STATS314A idk too hard
Modern Applied Statistics: Learning STATS315A idk too hard
Modern Applied Statistics: Learning II STATS315B idk too hard
Stochastic Processes STATS317 idk too hard
Modern Markov Chains STATS318 idk too hard
Literature of Statistics STATS319 idk too hard
Introduction to R for Undergraduates STATS32 idk too hard
Machine Learning Methods for Neural Data Analysis STATS320 idk too hard
Function Estimation in White Noise STATS322 idk too hard
Sequential Analysis STATS323 idk too hard
Stein's Method STATS324 idk too hard
Multivariate Analysis and Random Matrices in Statistics STATS325 idk too hard
Topics in Generative Modeling Methods in Protein Modeling and Design STATS326 idk too hard
Survival Analysis STATS331 idk too hard
Mathematics and Statistics of Gambling STATS334 idk too hard
The Challenge Problems Paradigm in Empirical Machine Learning and Beyond STATS335 idk too hard
Topics in Computing for Data Science STATS352 idk too hard
Causal Inference STATS361 idk too hard
Topic: Monte Carlo STATS362 idk too hard
Design of Experiments STATS363 idk too hard
Empirical Likelihood STATS365 idk too hard
Methods from Statistical Physics STATS369 idk too hard
Bayesian Statistics STATS370 idk too hard
Applied Bayesian Statistics STATS371 idk too hard
Mathematical Problems in Machine Learning STATS375 idk too hard
Consulting Workshop STATS390 idk too hard
Industrial Research for Statisticians STATS398 idk too hard
Research STATS399 idk too hard
Riding the Data Wave STATS48N idk too hard
Introduction to Statistical Methods: Precalculus STATS60 idk too hard
TGR Project STATS801 idk too hard
TGR Dissertation STATS802 idk too hard
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