## Course Website Locator: bio222-01

Harvard School of Public Health

The following course websites match your request:

### Fall 2009

#### Basics of Statistical Inference

Dr. P. Williams

5 credits

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

This course will provide a basic, yet thorough introduction to the probability theory and mathematical statistics that underlie many of the commonly used techniques in public health research. Topics to be covered include probability distributions (normal, binomial, Poisson), means, variances and expected values, finite sampling distributions, parameter estimation (method of moments, maximum likelihood), confidence intervals, hypothesis testing (likelihood ratio, Wald and score tests). All theoretical material will be motivated with problems from epidemiology, biostatistics, environmental health and other public health areas. This course is aimed towards second year doctoral students in fields other than Biostatistics. Background in algebra and calculus required.

Course Note: One intermediate level biostatistics course such as BIO 210, or BIO 211, or signature of the instructor required; lab or section times to be announced at first meeting. (5.06)

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.

### Fall 2008

#### Basics of Statistical Inference

Dr. P. Williams

5 credits

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

This course will provide a basic, yet thorough introduction to the probability theory and mathematical statistics that underlie many of the commonly used techniques in public health research. Topics to be covered include probability distributions (normal, binomial, Poisson), means, variances and expected values, finite sampling distributions, parameter estimation (method of moments, maximum likelihood), confidence intervals, hypothesis testing (likelihood ratio, Wald and score tests). All theoretical material will be motivated with problems from epidemiology, biostatistics, environmental health and other public health areas. This course is aimed towards second year doctoral students in fields other than Biostatistics. Background in algebra and calculus required.

Course Note: One intermediate level biostatistics course such as BIO 210, or BIO 211, or signature of the instructor required; lab or section times to be announced at first meeting. (5.06)

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.

### Fall 2007

#### Basics of Statistical Inference

Dr. P. Williams

5 credits

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

This course will provide a basic, yet thorough introduction to the probability theory and mathematical statistics that underlie many of the commonly used techniques in public health research. Topics to be covered include probability distributions (normal, binomial, Poisson), means, variances and expected values, finite sampling distributions, parameter estimation (method of moments, maximum likelihood), confidence intervals, hypothesis testing (likelihood ratio, Wald and score tests). All theoretical material will be motivated with problems from epidemiology, biostatistics, environmental health and other public health areas. This course is aimed towards second year doctoral students in fields other than Biostatistics. Background in algebra and calculus required.

Course Note: One intermediate level biostatistics course such as BIO 210, or BIO 211, or signature of the instructor required; lab or section times to be announced at first meeting. (5.06)

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.

### Fall 2006

#### Basics of Statistical Inference

Dr. Yi Li

5 credits

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

This course will provide a basic, yet thorough introduction to the probability theory and mathematical statistics that underlie many of the commonly used techniques in public health research. Topics to be covered include probability distributions (normal, binomial, Poisson), means, variances and expected values, finite sampling distributions, parameter estimation (method of moments, maximum likelihood), confidence intervals, hypothesis testing (likelihood ratio, Wald and score tests). All theoretical material will be motivated with problems from epidemiology, biostatistics, environmental health and other public health areas. This course is aimed towards second year doctoral students in fields other than Biostatistics. Background in algebra and calculus required.

Course Note: One intermediate level biostatistics course such as BIO 210, or BIO 211, or signature of the instructor required; lab or section times to be announced at first meeting. (5.06)

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.