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Home Academics Undergraduate Programs Statistics Minor

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Statistics Minor

A minor in Statistics is a good fit for students looking to learn the fundamentals of statistics and analyzing data.

As a Statistics minor, you will analyze data and learn the fundamental formulas needed in statistics. You will develop skills that can be applied to a wide range of topics such as marketing, heath science, nursing, education, and more.

Benefits of a Statistics Minor

  1. Apply Statistical skills to different fields of studies and career opportunities
  2. Understand the foundation of statistics and apply the correct principles to analyze data

Statistics Minor Requirements

These requirements are from an excerpt from the University Academic Catalog, which outlines the requirements for a student to earn the distinction of being a Castleton University graduate. The complete catalog is available online.

The Statistics Minor is offered by the Mathematics Department.

Complete the following courses (9 cr):

Code Course Credits

MAT 2021

Statistics I

This course prepares students for quantitative methods in their respective fields. Descriptive and inferential statistics, including estimation, hypothesis testing, linear regression and correlation are covered. Basic tools of descriptive statistics, discrete probability, binomial distribution, normal distribution, t-distribution, estimates and sample sizes, hypothesis testing, elementary correlation and regression, contingency tables are explored. Students utilize graphing calculators and spreadsheet software on a regular basis.

This course fulfills a Mathematics general education requirement.

Every semester

3

MAT 2022

Statistics II

This course is a continuation of MAT 2021 and includes estimation, hypothesis testing, single linear regression, and one-way analysis of variance using calculators and statistical software. This course addresses in-depth such topics as the Central Limit Theorem, Chebyshev's theorem, covariance, multiple regression, ANOVA, nonparametric methods, and applications of probability distributions. It includes problems dealing with multiple linear regression, multi-way analysis of variance, nonparametric statistics, enumerative data, and computer applications. Students utilize graphing calculators and spreadsheet software on a regular basis.

Prerequisite: MAT 2021

Every semester

3

MAT 3250

Applied Statistics with SPSS

Methods of analyzing univariate and multivariate data using statistical packages including Minitab, SPSS, and SAS. Topics include descriptive statistics for univariate and bivariate data, basic properties of multivariate distributions, multivariate linear regression, principal component analysis for dimension reduction, factor analysis, canonical correlation analysis, discrimination and classification, and simple multiple series models.

Prerequisite: MAT 2022 or MAT 3230

Every Semester

3

And complete 1 of the following courses (3-4 cr):

Code Course Credits

MAT 1530

Applied Calculus

An introduction to calculus intended primarily for students in business, science, and the social sciences. Topics include functions, limits, continuity, differentiation, applications of derivatives, antiderivatives, definite integral and the Fundamental Theorem of Calculus.

This course fulfills a Mathematics general education requirement.

Prerequisite: MAT 1360 or appropriate placement

Fall

3

MAT 1531

Calculus I

Topics include limits, differentiation, applications of derivatives, and an introduction to integration. This course may utilize graphing calculators on a regular basis.

This course fulfills a Mathematics general education requirement.

Prerequisite: MAT 1360 or equivalent.

Every semester

4

And complete at least 6 credits from the following:

Code Course Credits

BUS 4030

Marketing Research

An overview of the process of assembling information to make better marketing decisions. Topics include measurement principles, research designs, sampling techniques, data collection and analysis.

Prerequisite: BUS 2230, and either BUS 2550 or MAT 2021 and MAT 2022.

Fall

3

BUS 4110

Operations Management

Introduction to concepts and fundamental understanding of systems management. Study of specific problems; decision-making processes dealing with planning and control in manufacturing and service firms.

Prerequisite: BUS 2550 or MAT 2021 and MAT 2022

Fall

3

BUS 4130

Quantitative Business Decisions

Mathematical business decision-making techniques and methods of problem analysis of decision made under uncertainty. Individuals participating in the 4-Plus1 MBA program with Clarkson University must take this course.

Prerequisite: BUS 2550 or MAT 2021 and MAT 2022

Spring

3

CHE 2111

Organic Chemistry I

An introduction to the chemistry of organic compounds. Emphasis is on organic functional groups and their chemical properties, nomenclature and molecular structure. The laboratory introduces students to basic organic laboratory techniques of synthesis, purification and characterization. Lecture (3 hrs.) and lab (4 hrs). Students are strongly recommended to take Organic Problem Solving I (CHE 2113) together with this course.

Prerequisite: CHE 1042 or CHE 1052 with a grade of C or better.

Fee Lab fee $50.

Fall

4

CHE 2112

Organic Chemistry II

A continuation of CHE 2111. Continued study of organic functional groups and their chemical properties and molecular structures. Emphasis is on reaction mechanisms, aromaticity and spectroscopic methods od analysis of organic molecules. Students are strongly recommended to take Organic Problem Solving II ( CHE 2114 ) together with this course.

Lecture (3 hrs) and lab (4 hrs).

Prerequisite: CHE 2111

Fee Lab fee $50.

Spring

4

MAT 4010

Design of Experiments

Analysis of Variance techniques, basic experimental designs, complete and incomplete blocking, and factorial designs.

Prerequisite: MAT 2022 or MAT 3230. Marketing Majors should elect this course after BUS 4030.

Periodically

3

MAT 4020

Applied Linear Regression

Linear and multiple regression models. Least squares estimates, correlation, and prediction. Discriminate analysis, factor analysis, and cluster analysis.

Prerequisite: MAT 1531, MAT 3250.

Periodically

3

POS 2510

Research Methods

This course provides students with a broad understanding of how research is conducted in social science disciplines, focusing on the discipline of Political Science. Students will become aware of a wide array of research tools available to address questions in the study of politics and government. More importantly, they will learn how to select the appropriate research tools based on the nature of the research question being addressed. The course begins with the study of how to frame research questions, formulate hypotheses, and then test hypotheses. Next, we explore the nature of data (quantitative and qualitative) and approaches in the rigorous collection of data. We also review many existing data sources for secondary analysis.

Fall, even years

3

POS 3510

Quantitative Analysis

This course provides students with the knowledge and skills to conduct quantitative research in Political Science. Students will work with SPSS software to perform data analysis, learning how to produce and interpret statistical procedures. The scope of the class proceeds from understanding variability in frequency distributions and measures of central tendency to multi-variate and logistic regression analysis.

This course fulfills a Digital and Computing Literacy general education requirement.

Prerequisite: POS 2510 and MAT 2021

Spring, odd years

3

SOC 3910

Research Methods

  • or other courses approved by the Mathematics Department

Introduction to the basic methods of sociological research design, data collection, the organization and analysis of data, and their interpretation through an actual research project.

This course fulfills the Digital and Computing Literacy general education requirement.

Prerequisite: Junior majors in SOC, CRJ or acceptance in Social Work program, or consent of instructor.

Fall and Spring

4

(Total credits required: 18-19)

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