# Courses in Statistics (Division 489)

## Calendars

### Summer Half-Term

This page was created at 2:56 PM on Mon, Aug 14, 2000.

## Spring Half-Term Courses

Take me to the Spring Half-Term '00 Time Schedule for Statistics.

#### To see what has been added or changed in Statistics this week go to What's New This Week.

Search the LS&A Spring Half-Term Course Guide (Advanced Search Page)

### Stat. 100. Introduction to Statistical Reasoning.

#### Instructor(s): Brenda Gunderson (bkg@umich.edu)

Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in Soc. 210, Stat. 265, 311, 402, 405, or 412, or Econ. 404 or 405. (4). (MSA). (BS). (QR/1).

Credits: (4).

Course Homepage: http://www.stat.lsa.umich.edu/~bkg/100SP00/

This course is designed to provide an overview of the field of statistics. Course topics include methods of analyzing and summarizing data, statistical reasoning as a means of learning from observations (experimental or sample), and techniques for dealing with uncertainties in drawing conclusions from collected data. Basic fallacies in common statistical analyses and reasoning are discussed and proper methods indicated. The course emphasis is on presenting basic underlying concepts rather than on covering a wide variety of different methodologies. Course evaluation is based on a combination of a midterm exam, a final exam, in-class quizzes, weekly homework, and lab participation. The course format includes three lectures (6 hours per week) and a laboratory (2 hours per week).

### Stat. 265/IOE 265. Probability and Statistics for Engineers.

#### Instructor(s): Grasman

Prerequisites & Distribution: Math. 116 and Engin. 101. No credit granted to those who have completed or are enrolled in Stat. 311, 405, or 412, or Econ. 405. (Excl). (BS). CAEN lab access fee required for non-Engineering students.

Credits: (4).

Lab Fee: CAEN lab access fee required for non-Engineering students.

Course Homepage: No Homepage Submitted.

Graphical representation of Data; axioms of Probability; conditioning, Bayas Theorem; discreet distributions (Geometric, Binomial, Poisson); continuous distributions (normal exponential, Weibull), point and interval estimation, likelihood functions, test of hypotheses for Means, Variances, and Proportions for one and two populations. Regular homework and a final exam.

 Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

### Stat. 402. Introduction to Statistics and Data Analysis.

#### Instructor(s): Brenda Gunderson (bkg@umich.edu)

Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in Econ. 404 or 405, or Stat. 265, 311, 405, or 412. (4). (NS). (BS). (QR/1).

Credits: (4).

Course Homepage: http://www.stat.lsa.umich.edu/~bkg/402SP00/

In this course students are introduced to the concepts and applications of statistical methods and data analysis. Statistics 402 has no prerequisite and has been elected by students whose mathematics background includes only high school algebra. Examples of applications are drawn from virtually all academic areas and some attention is given to statistical process control methods. The course format includes lectures (6 hours per week) and a laboratory (3 hours per week). The laboratory section deals with the computational aspects of the course and provides a forum for review of lecture material. For this purpose, students are introduced to the use of a statistical analysis-computer package. Course evaluation is based on a combination of a midterm exam, a final exam, in-class quizzes, weekly homework, and lab participation.

### Stat. 412. Introduction to Probability and Statistics.

#### Instructor(s): Anil Gore (anilg@umich.edu)

Prerequisites & Distribution: Prior or concurrent enrollment in Math. 215 and CS 183. No credit granted to those who have completed or are enrolled in Econ. 405, or Stat. 265, 311, or 405. One credit granted to those who have completed Stat. 402. (3). (MSA). (BS).

Credits: (3).

Course Homepage: No Homepage Submitted.

The objectives of this course are to introduce students to the basic ideas of probability and statistical inference and to acquaint students with some important data analytic techniques, such as regression and the analysis of variance. Examples will emphasize applications to the natural sciences and engineering. There will be regular homework, two midterms, and a final exam.

 Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

### Stat. 425/Math. 425. Introduction to Probability.

#### Instructor(s):

Prerequisites & Distribution: Math. 215, 255, or 285. (3). (MSA). (BS).

Credits: (3).

Course Homepage: No Homepage Submitted.

See Mathematics 425..

 Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

### Stat. 499. Honors Seminar.

#### Instructor(s):

Prerequisites & Distribution: Permission of departmental Honors advisor. (2-3). (Excl). (INDEPENDENT).

Credits: (2-3).

Course Homepage: No Homepage Submitted.

 Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

## Spring/Summer Term Courses

Take me to the Spring/Summer Term '00 Time Schedule for Statistics.
Search the LS&A Spring/Summer Term Course Guide (Advanced Search Page)

## Summer Half-Term Courses

Take me to the Summer Half-Term '00 Time Schedule for Statistics.

Search the LS&A Summer Half-Term Course Guide (Advanced Search Page)

### Stat. 100. Introduction to Statistical Reasoning.

#### Instructor(s):

Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in Soc. 210, Stat. 265, 311, 402, 405, or 412, or Econ. 404 or 405. (4). (MSA). (BS). (QR/1).

Credits: (4).

Course Homepage: No Homepage Submitted.

This course is designed to provide an overview of the field of statistics. Course topics include methods of analyzing and summarizing data, statistical reasoning as a means of learning from observations (experimental or sample), and techniques for dealing with uncertainties in drawing conclusions from collected data. Basic fallacies in common statistical analyses and reasoning are discussed and proper methods indicated. Alternative approaches to statistical inference are also discussed. The course emphasis is on presenting basic underlying concepts rather than on covering a wide variety of different methodologies. The course format is six hours of lecture per week and two hours of laboratory per week.

 Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

### Stat. 402. Introduction to Statistics and Data Analysis.

#### Instructor(s):

Prerequisites & Distribution: No credit granted to those who have completed or are enrolled in Econ. 404 or 405, or Stat. 265, 311, 405, or 412. (4). (NS). (BS). (QR/1).

Credits: (4).

Course Homepage: No Homepage Submitted.

In this course students are introduced to the concepts and applications of statistical methods and data analysis. Statistics 402 has no prerequisite and has been elected by students whose mathematics background includes only high school algebra. Examples of applications are drawn from virtually all academic areas and some attention is given to statistical process control methods. The course format includes six hours of lecture per week and three hours of laboratory per week. The laboratory section deals with the computational aspects of the course and provides a forum for review of lecture material. For this purpose, students are introduced to the use of a microcomputer package and the Macintosh computer.

 Check Times, Location, and Availability Cost: No Data Given. Waitlist Code: No Data Given.

### Stat. 425/Math. 425. Introduction to Probability.

#### Instructor(s):

Prerequisites & Distribution: Math. 215, 255, or 285. (3). (MSA). (BS).

Credits: (3).

Course Homepage: No Homepage Submitted.

No Description Provided

Check Times, Location, and Availability

This page was created at 2:57 PM on Mon, Aug 14, 2000.