## Course Website Locator: bio201-01

Harvard T.H. Chan School of Public Health

The following course websites match your request:

### Fall 2009

#### Introduction to Statistical Methods

Dr. K. Gauvreau

5 credits

Lectures, laboratories. Two 1.5-hour sessions each week. One 2-hour lab each week.

Covers basic statistical techniques that are important for analyzing data arising from epidemiology, environmental health and biomedical and other public health-related research. Major topics include descriptive statistics, elements of probability, introduction to estimation and hypothesis testing, nonparametric methods, techniques for categorical data, regression analysis, analysis of variance, and elements of study design. Applications are stressed. Designed as an alternate to BIO200, for students desiring more emphasis on theoretical developments. Background in algebra and calculus strongly recommended.

Course Note: Credit is given for only one of BIO200 or BIO201; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students enrolled in DBS, EH, EPI, NUT, MPH/QM programs, and SHDH doctoral students. Other students allowed with signature of course instructor if space permits; lab or section times to be announced at first meeting.

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

### Fall 2008

#### Introduction to Statistical Methods

Dr. K. Gauvreau

5 credits

Lectures, laboratories. Two 1.5-hour sessions each week. One 2-hour lab each week.

Covers basic statistical techniques that are important for analyzing data arising from epidemiology, environmental health and biomedical and other public health-related research. Major topics include descriptive statistics, elements of probability, introduction to estimation and hypothesis testing, nonparametric methods, techniques for categorical data, regression analysis, analysis of variance, and elements of study design. Applications are stressed. Designed as an alternate to BIO200, for students desiring more emphasis on theoretical developments. Background in algebra and calculus strongly recommended.

Course Note: Credit is given for only one of BIO200 or BIO201; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students enrolled in DBS, EH, EPI, NUT, MPH/QM programs, and SHDH doctoral students. Other students allowed with signature of course instructor if space permits; lab or section times to be announced at first meeting.

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

### Fall 2007

#### Introduction to Statistical Methods

Dr. K. Gauvreau

5 credits

Lectures, laboratories. Two 1.5-hour sessions each week. One 2-hour lab each week.

Covers basic statistical techniques that are important for analyzing data arising from epidemiology, environmental health and biomedical and other public health-related research. Major topics include descriptive statistics, elements of probability, introduction to estimation and hypothesis testing, nonparametric methods, techniques for categorical data, regression analysis, analysis of variance, and elements of study design. Applications are stressed. Designed as an alternate to BIO200, for students desiring more emphasis on theoretical developments. Background in algebra and calculus strongly recommended.

Course Note: Credit is given for only one of BIO200 or BIO201; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students enrolled in DBS, EH, EPI, NUT, MPH/QM programs, and SHDH doctoral students. Other students allowed with signature of course instructor if space permits; lab or section times to be announced at first meeting.

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

### Fall 2006

#### Introduction to Statistical Methods

Dr. K. Gauvreau

5 credits

Lectures, laboratories. Two 1.5-hour sessions each week. One 2-hour lab each week.

Covers basic statistical techniques that are important for analyzing data arising from epidemiology, environmental health and biomedical and other public health-related research. Major topics include descriptive statistics, elements of probability, introduction to estimation and hypothesis testing, nonparametric methods, techniques for categorical data, regression analysis, analysis of variance, and elements of study design. Applications are stressed. Designed as an alternate to BIO200, for students desiring more emphasis on theoretical developments. Background in algebra and calculus strongly recommended.

Course Note: Credit is given for only o

ne of BIO200 or BIO201; this course cannot be counted as part of the credit requirement for a major or minor doctoral field course; course restricted to students enrolled in DBS, EH, EPI, NUT, MPH/QM programs, and SHDH doctoral students. Other students allowed with signature of course instructor if space permits; lab or section times to be announced at first meeting. (6.06)

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.