Course Description: Graphical and numerical descriptive methods; Interpretation of probability; Basic ideas in random sampling methods and experimental design; Random error and sources of bias in surveys; Sampling distributions; Confidence intervals and significance tests for single mean, single proportion, and difference between two means or two proportions; Correlation; Descriptive and inferential simple linear regression. Throughout the course, students will interpret output from statistical software packages, including R and Minitab. Students may not count graduation credit for both MATH 105 and PSYC 210. This course cannot be taken after receiving credit for MATH 110 or above. Proficiency credit for MATH 110 or MATH 111 may not be awarded after credit for MATH 105. (Quantitative)
Course Delivery- Hybrid: All lecture materials (slide presentations and videos) will be available via Blackboard. Students will attend in-person lectures one or two days a week with the other day of instruction being delivered remotely. These in person lectures will be for class discussion as well as going over specific examples with students. Sessions will be recorded and available for students at the instructor's discretion. All assignments will be available and submitted via Blackboard.
Course Description: Graphical and numerical descriptive methods; Interpretation of probability; Basic ideas in random sampling methods and experimental design; Random error and sources of bias in surveys; Sampling distributions; Confidence intervals and significance tests for single mean, single proportion, and difference between two means or two proportions; Correlation; Descriptive and inferential simple linear regression. Throughout the course, students will interpret output from statistical software packages, including R and Minitab. Students may not count graduation credit for both MATH 105 and PSYC 210. This course cannot be taken after receiving credit for MATH 110 or above. Proficiency credit for MATH 110 or MATH 111 may not be awarded after credit for MATH 105. (Quantitative)
Course Delivery- Hybrid: All lecture materials (slide presentations and videos) will be available via Blackboard. Students will attend in-person lectures one or two days a week with the other day of instruction being delivered remotely. These in person lectures will be for class discussion as well as going over specific examples with students. Sessions will be recorded and available for students at the instructor's discretion. All assignments will be available and submitted via Blackboard.
Course Description: Graphical and numerical descriptive methods; Interpretation of probability; Basic ideas in random sampling methods and experimental design; Random error and sources of bias in surveys; Sampling distributions; Confidence intervals and significance tests for single mean, single proportion, and difference between two means or two proportions; Correlation; Descriptive and inferential simple linear regression. Throughout the course, students will interpret output from statistical software packages, including R and Minitab. Students may not count graduation credit for both MATH 105 and PSYC 210. This course cannot be taken after receiving credit for MATH 110 or above. Proficiency credit for MATH 110 or MATH 111 may not be awarded after credit for MATH 105. (Quantitative)
Course Delivery- Hybrid: I'd like to alternate days in which we meet in the classroom and when we meet remotely. The balance may shift over time, more in-person meetings when I feel it's safe or best, more remote meetings otherwise. ALL meetings (on campus in the classroom, or remote) will be synchronous, held during the assigned class time. At the beginning of every class meeting, I'll start a Zoom session and invite the whole class. I'll use my iPad to write notes and discuss the lecture... and this will be projected both to the classroom screen (on days when we're in class) and to the Zoom classroom. The Zoom session meetings will also be recorded and posted to my Google drive, which will be linked on the Google classroom so that students that miss a session have access to it. Attendance at synchronous meetings will be required of all students. Not approved for an entirely remote experience.
Course Description: A detailed treatment of differential calculus including limits, continuity, derivatives, and applications of derivatives (rates of change, related rates, curve sketching, and optimization). The course also gives an introduction to integrals, including area, Riemann sums, and the Fundamental Theorem of Calculus. The course assumes familiarity with the transcendental functions, as they appear throughout. Symbolic algebra software may be introduced and used. Students wishing to major in mathematics or computer science are urged to take this course in the fall of their freshman year. (Group II) (Quantitative)
Course Delivery:
Course Description: A detailed treatment of differential calculus including limits, continuity, derivatives, and applications of derivatives (rates of change, related rates, curve sketching, and optimization). The course also gives an introduction to integrals, including area, Riemann sums, and the Fundamental Theorem of Calculus. The course assumes familiarity with the transcendental functions, as they appear throughout. Symbolic algebra software may be introduced and used. Students wishing to major in mathematics or computer science are urged to take this course in the fall of their freshman year. (Group II) (Quantitative)
Course Delivery:
Course Description: Continuation of MATH 110. A detailed treatment of integral calculus, including integration techniques, numerical integration, applications of integration, an introduction to differential equations, parametric equations, polar coordinates, and infinite sequences and series. Symbolic algebra software may be introduced and used. Prerequisite: MATH 110. (Group II) (Quantitative)
Course Delivery: Fully Remote
Course Description: Vectors and geometry of three-dimensional space, partial derivatives, multiple integrals, and an introduction to vector analysis. Computer symbolic algebra projects are included. Prerequisite: MATH 111. (Group II) (Quantitative)
Course Delivery: Fully Remote
Course Description: Introductory course in statistics. Exploratory data analysis, questions of causation, probability, continuous and discrete random variables, distributions of sums of random variables, sampling distributions, one and two-sample confidence intervals and significance tests, limitations of inference, model selection and inference in simple and multiple linear regression. Students may count for graduation credit only one of the courses MATH 105, MATH 200 3, MATH 230, and PSYC 210. Prerequisite: MATH 110. (Group II) (Quantitative)
Course Delivery- Hybrid: I'd like to alternate days in which we meet in the classroom and when we meet remotely. The balance may shift over time, more in-person meetings when I feel it's safe or best, more remote meetings otherwise. ALL meetings (on campus in the classroom, or remote) will be synchronous, held during the assigned class time. At the beginning of every class meeting, I'll start a Zoom session and invite the whole class. I'll use my iPad to write notes and discuss the lecture... and this will be projected both to the classroom screen (on days when we're in class) and to the Zoom classroom. The Zoom session meetings will also be recorded and posted to my Google drive, which will be linked on the Google classroom so that students that miss a session have access to it. Attendance at synchronous meetings will be required of all students not approved for an entirely remote experience.
Course Description: An introduction to mathematical reasoning and to the kind of mathematics appropriate for the study of properties of (possibly large) finite systems. Topics include proof techniques, mathematical induction, elementary number theory, combinatorics, relations, and graph theory. Applications will be made to the construction of models useful in the social and physical sciences and to the study of algorithms in computer science. Prerequisite: MATH 111 (Group II)
Course Delivery- Hybrid: As far as possible, I'm hoping to teach the course in person. The bit after Thanksgiving will be online. I really hope that we can make it to Thanksgiving for in person instruction; I'm happy that we can at least begin in this manner.
Course Description: Rigorous development of the topology of the real line, theory of metric spaces, and the foundations of calculus. Attention is given to constructing formal proofs. Prerequisite: MATH 210 and MATH 250. Recommended: MATH 270.
Course Delivery:
Course Description: An introduction to mathematical reasoning and to the kind of mathematics appropriate for the study of properties of (possibly large) finite systems. Topics include proof techniques, mathematical induction, elementary number theory, combinatorics, relations, and graph theory. Applications will be made to the construction of models useful in the social and physical sciences and to the study of algorithms in computer science. Prerequisite: MATH 111 (Group II)
Course Delivery- Hybrid: I'd like to alternate days in which we meet in the classroom and when we meet remotely. The balance may shift over time, more in-person meetings when I feel it's safe or best, more remote meetings otherwise. ALL meetings (on campus in the classroom, or remote) will be synchronous, held during the assigned class time. At the beginning of every class meeting, I'll start a Zoom session and invite the whole class. I'll use my iPad to write notes and discuss the lecture... and this will be projected both to the classroom screen (on days when we're in class) and to the Zoom classroom. The Zoom session meetings will also be recorded and posted to my Google drive, which will be linked on the Google classroom so that students that miss a session have access to it. Attendance at synchronous meetings will be required of all students not approved for an entirely remote experience.