11 Statistics Course Programs

Introduces basic statistical modeling techniques. One- or two- sample inference for unknown means, proportions and variances, categorical data analysis, introduction to design of experiments and analysis of variance, analysis of simple and multiple linear regression models, non-parametric methods.

Introduction to the logic and processes involved in descriptive and inferential statistics for psychology. Topics include statistical inference, significance, t-tests, ANOVAs, correlation, regression, and statistical software analysis. This is a hybrid class: class time is reserved for hands-on activities.

Undergraduate Prerequisites: Academic background that includes the material covered in a standard course on college algebra.

Elementary treatment of probability densities, means, variances, correlation, independence, the central limit theorem, confidence intervals, and p-values. Students learn to answer questions such as how can a pollster use a sample to predict the uncertainty of an election?

We offer courses that, in the true spirit of the liberal arts, emphasize underlying ideas, their social and ethical context, and their explanatory power. The statistics major emphasizes a strong background in the fundamentals, while also providing pathways to explore how statistics is applied in a variety of fields. Statistics is a core component of many fields from medicine to economics to data science.

The Master of Arts and Master of Science degrees in Applied Statistics provide students with the necessary background to seek employment in statistics, data sciences or a related field. The degree programs provide training in applied statistics and consulting, as well as in the theory of statistics pertinent to applications. In addition, students are required to study an approved area outside of statistics at the graduate level. Possible areas include numerical analysis, biostatistics, education, economics, sociology, psychology, biology, business, bioinformatics, computer science, mathematical finance, and many others.

The Applied Statistics B.A. is designed for students to learn the skills necessary to work in fields such as Economics, Psychology & Biology. Applied Statistics is for students interested in pursuing other disciplines in the field of Statistics such as Economics, Psychology and Biology. The curriculum is focused for students pursuing a B.A. or a Minor in Applied Statistics through practical skills such as regression analysis and ANOVA, or gaining experience in statistical software such as SAS and SPSS.

Kenyon’s mathematics program blends theoretical ideas and methods, the modeling of real-world situations, and the statistical analysis of data. Members of the mathematics faculty are at the forefront of such innovative programs as mathematical biology and work closely with students on research projects.

The focus of our courses is on the broad understanding of the statistical methods and computational and presentation skills for statistical problem-solving. We also develop students’ ability to systematically think about how to describe the world around us and use data to make decisions and predictions. Statistical research methodology and associated analysis techniques aimed at a non-mathematical audience (non-calculus based). This course introduces procedures that are most commonly used in the investigation of survey and experimental data.

The broad objective of the course is to promote an understanding of an objective and disciplined approach in the study and analysis of problems especially those involving numerical data in experimental studies. The course covers: organization and presentation of numerical data, descriptive statistics, concepts of parameter and statistic, distribution of sample means, hypothesis and test of hypothesis, student's t-distribution, confidence interval and coefficient, x2-distribution, F-distribution, analysis of variance, randomized block design, simple regression and correlation.

The M.S. in Quantitative Methods in the Social Sciences at the Graduate Center prepares students from a variety of backgrounds for a data-driven future. Data analysis is driving research and decision-making in every social science field and sector. The M.S. in Quantitative Methods in the Social Sciences at the Graduate Center prepares students from a variety of backgrounds for a data-driven future.