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Transcript
COURSE SYLLABUS
Ohio Northern University
College of Arts and Sciences
Department of Mathematics and Statistics
Date: Fall 2011
Course Stat 2501
Name: Statistics for Scientists and Engineers
Credit hours: 3
Lecture hours/week: 3
Lab hours/week: 0
Instructor: Staff
Usual Student Level: Sophomore and above
Course required of students in: College of Engineering
Course frequency per semester/year: Offered Fall and Spring Semesters every year
Average enrollment per year: 125
This course has a prerequisite:
Math 1641
This course is a prerequisite for:
Stat 2561
Catalogue Description:
Basic statistical techniques; Random variables and their distributions; Statistical inference (point
estimation, confidence intervals, hypothesis testing); Statistical study designs; Linear regression and
analysis of variance methods.
Course Objectives:
Learn concepts and models of probability, as well as basic statistical techniques of confidence intervals
and hypothesis testing.
Textbook: “Miller and Freund’s Statistics for Engineers” by Miller , Freund (Pearson / Prentice Hall 8e)
Outline of content follows:
Course Outline
Stat 2501
Statistics for Scientists and Engineers
Introduction to Statistics
Descriptive statistics (including tabular and graphical methods)
Concepts of probability (including binomial, normal, hypergeometric, Poisson, geometric,
exponential, and gamma distributions)
Sampling distribution (including central limit theorem)
Bivariate data (brief discussion of correlation and regression for 2 quantitative variables)
Point estimation, confidence intervals, and hypotheses tests:
for a single mean
for the difference between two means (independent and paired samples)
for the ratio of two variances (optional)
for a single proportion and the difference of two proportions (both optional)
Study design
Experimental vs. observational designs
Completely randomized vs. randomized block experimental designs
Matched vs. unmatched data
Simple linear regression and correlation (optional)
Least squares estimation
Inferences for regression parameters
Single-factor Analysis of Variance (optional)
Remarks
1. In general, emphasis should be on “statistical reasoning” as opposed to “statistical calculations”.
2. The TI-83 or 84 calculator is required for this course. Please do not use built-in STAT functions to
compute confidence intervals or perform hypothesis tests until after the students have mastered
these concepts.