Emily Malcolm-White
Office
Warner 215
Tel
(802) 443-2196
Email
emalcolmwhite@middlebury.edu
Office Hours
Fall 2022: Mondays, Tuesdays, and Wednesdays 2:45 - 4pm in WNS 215 or by appointment: https://calendly.com/emilymw/15-minutes-online (via Zoom) or https://calendly.com/emilymw/15-min-in-person (in Person)
Additional Programs
Mathematics

Courses Taught

Course Description

Introduction to Statistical Science
A practical introduction to statistical methods and the examination of data sets. Computer software will play a central role in analyzing a variety of real data sets from the natural and social sciences. Topics include descriptive statistics, elementary distributions for data, hypothesis tests, confidence intervals, correlation, regression, contingency tables, and analysis of variance. The course has no formal mathematics prerequisite, and is especially suited to students in the physical, social, environmental, and life sciences who seek an applied orientation to data analysis. (Credit is not given for MATH 0116 if the student has taken ECON 0111 (formerly ECON 0210) or PSYC 0201 previously or concurrently.) 3 hrs. lect./1 hr. computer lab.

Terms Taught

Fall 2019, Spring 2020, Spring 2021, Fall 2021, Spring 2022, Spring 2023

Requirements

DED

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Course Description

Introduction to Data Science
In this course students will gain exposure to the entire data science pipeline: forming a statistical question, collecting and cleaning data sets, performing exploratory data analyses, identifying appropriate statistical techniques, and communicating the results, all the while leaning heavily on open source computational tools, in particular the R statistical software language. We will focus on analyzing real, messy, and large data sets, requiring the use of advanced data manipulation/wrangling and data visualization packages. Students will be required to bring alaptop (owned or college-loaned) to class as many lectures will involve in-class computational activities. (formerly MATH216) 3 hrs lect./disc.

Terms Taught

Fall 2022, Spring 2023

Requirements

DED

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Course Description

Calculus I
Introductory analytic geometry and calculus. Topics include limits, continuity, differential calculus of algebraic and trigonometric functions with applications to curve sketching, optimization problems and related rates, the indefinite and definite integral, area under a curve, and the fundamental theorem of calculus. Inverse functions and the logarithmic and exponential functions are also introduced along with applications to exponential growth and decay. 4 hrs. lect./disc.

Terms Taught

Fall 2019, Fall 2020, Fall 2021, Fall 2022

Requirements

DED

View in Course Catalog

Course Description

Introduction to Data Science
In this course students will gain exposure to the entire data science pipeline: forming a statistical question, collecting and cleaning data sets, performing exploratory data analyses, identifying appropriate statistical techniques, and communicating the results, all the while leaning heavily on open source computational tools, in particular the R statistical software language. We will focus on analyzing real, messy, and large data sets, requiring the use of advanced data manipulation/wrangling and data visualization packages. Students will be required to bring their own laptops as many lectures will involve in-class computational activities. 3 hrs lect./disc.

Terms Taught

Spring 2020

Requirements

DED

View in Course Catalog