Statistics

Statistics is the science of learning from data. It has been a rapidly growing science for many years. It is widely used by businesses and government organizations to understand changes in the economy and to make forecasts about future events based on past patterns in their data. The methodology of statistics can be adapted to many types of problems. Due to the extensive development of computers and the collection of large databases, the need for statistical techniques has greatly expanded in recent years. A society like ours, which has become increasingly dependent on its data, has a growing need for statisticians.

The Department of Statistics and Biostatistics offers a B.S. degree in statistics. Majors in this program study, collect, and analyze all types of data and report the results of the analysis.

 

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Your Future

Career Opportunities Include:

Actuary • Biostatistician • Business Analyst • Census Analyst • Credit Analyst • Customer Analytics Specialist • Data Analyst • Data Manager • Data Scientist • Data Visualization Designer • Educational Researcher • Financial Modeler • Information Systems Analyst • Marketing Analytics Specialist • Quality Control Specialist • R programmer • Research Statistician • Sales Analyst • Statistical Programmer • Sports Analyst • Statistician • Survey Designer • Systems Analyst • Teacher

 

Future Income:

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Courses You Might Take

STAT 315 - Exploring and Analyzing Data

Understand the foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. An introduction to statistical programming and statistical inference with hands-on analysis of real-world datasets.

STAT 321 - Probability Through Simulation

Learn introductory probability using simulation methods. Topics include the estimation and accuracy of probabilities using repeated sampling and simulating conditional probabilities using conditional programming techniques.

STAT 330 - Statistical Inference

Covers random variables, sampling distributions, confidence intervals, and conditional probability. Topics include t-tests, correlation, regression, chi-squared and ANOVA.

STAT 331 - Introduction to Analysis of Variance

Analysis of variance with emphasis on design and analysis of experiments. Uses data from social sciences, science, and business. Other topics include factorial designs, random effects, and nesting.

STAT 451 - Introduction to Data Visualization

Studies data visualization and interactive data exploration. Topics include importing, exporting and data merging, graphs and charts, interactive maps, and meaningful visual representations of complex statistics.

STAT 481 - Bayesian Statistics

Explores concepts and computation with real data applications. Topics include Bayes’ theorem, distributions, and hierarchical models. Computational strategies such as MCMC, model diagnostics and selection are discussed.

Contact Us

Department of Statistics & Biostatistics
  • 缅北禁地, East Bay
  • North Science 229
  • Hayward, CA 94542