Elementary vector calculus; introduction to partial derivatives; multiple integrals in two and three dimensions; line integrals in the plane; Green’s theorem; the Taylor development and extrema of functions of several variables; implicit function theorems; Jacobians. Four class hours per week.

(Offered as MATH 205, BLST 209 and HIST 209 [US].) This course will look at issues surrounding inequality in K-12 math education. Mathematics has a reputation for being something that either you can do or you can’t: the so-called "geniuses" know all the answers already, whereas for everyone else it is a constant struggle. In addition, math and other STEM fields have traditionally been discouraged as career paths for women and for students from underrepresented groups. At Amherst today, students from those groups are still in the minority in math classes.

(Offered as STAT 135 and MATH 135.)  Introduction to Statistics via Modeling is an introductory statistics course that uses modeling as a unifying framework.  The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, probability, study design, ANOVA, and multiple regression.

(Offered as STAT 135 and MATH 135.)  Introduction to Statistics via Modeling is an introductory statistics course that uses modeling as a unifying framework.  The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, probability, study design, ANOVA, and multiple regression.

(Offered as STAT 135 and MATH 135.)  Introduction to Statistics via Modeling is an introductory statistics course that uses modeling as a unifying framework.  The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, probability, study design, ANOVA, and multiple regression.

(Offered as STAT 135 and MATH 135.)  Introduction to Statistics via Modeling is an introductory statistics course that uses modeling as a unifying framework.  The course provides a basic foundation in statistics with a major emphasis on constructing models from data. Students learn important concepts of statistics by mastering powerful and relatively advanced statistical techniques using computational tools. Topics include descriptive and inferential statistics, probability, study design, ANOVA, and multiple regression.

A continuation of MATH 111. Inverse trigonometric and hyperbolic functions; methods of integration, both exact and approximate; applications of integration to volume and arc length; improper integrals; l’Hôpital’s rule; infinite series, power series and the Taylor development; and polar coordinates. Four class hours per week.

Requisite: A grade of C or better in MATH 111 or placement into MATH 121 or consent of the Department. Limited to 30 students per section. Fall and spring semesters. Both semesters. Professor Call and Lecturer D. Benedetto.

A continuation of MATH 111. Inverse trigonometric and hyperbolic functions; methods of integration, both exact and approximate; applications of integration to volume and arc length; improper integrals; l’Hôpital’s rule; infinite series, power series and the Taylor development; and polar coordinates. Four class hours per week.

Requisite: A grade of C or better in MATH 111 or placement into MATH 121 or consent of the Department. Limited to 30 students per section. Fall and spring semesters. Both semesters. Professor Call and Lecturer D. Benedetto.

Basic concepts of limits, derivatives, anti-derivatives; applications, including max/min problems and related rates; the definite integral, simple applications; trigonometric functions; logarithms and exponential functions. Four class hours per week.

MATH 106 is a continuation of MATH 105. Trigonometric, logarithmic and exponential functions will be studied from the point of view of both algebra and calculus. The applications encountered in MATH 105 will reappear in problems involving these new functions. The basic ideas and theorems of calculus will be reviewed in detail, with more attention being paid to rigor. Four class meetings per week, one of which is a two-hour group-work day.

Requisite: MATH 105. Spring semester. Lecturer D. Benedetto.