APPLIED STATISTICS FOR BIOMEDICAL ENGINEERS

Name: APPLIED STATISTICS FOR BIOMEDICAL ENGINEERS
Availability: OutOfStock
Rating: 4.7 (363 reviews)

BME 325

과목 설명

Learn and apply the fundamentals of descriptive and inferential statistics to analyze data and present the results in appropriate graphical formats. Emphasis will be on applications commonly encountered in biomedical engineering including t-tests, linear regression, analysis of variance, diagnostic tests, ROC curves, and methods for graphing and presenting data. Examples and practice problems will be drawn from biomedical research. Learn how to analyze data and interpret statistical analysis presented in research papers, and will get practical hands-on experience implementing these tools during class in a computer lab setting.

선수과목

Declared in Biomedical Engineering and MATH 222

충족 요건

STAT 303 , STAT 333 , ME 536 , and CIVENGR 516

학점

미보고

개설 시기

미보고

평점

3.78

0.78% 과거 데이터 대비

수료율

100%

0.55% 과거 데이터 대비

A 비율

71.01%

1.89% 과거 데이터 대비

학급 규모

14.05% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

INTRODUCTION TO BIOSTATISTICS

BMI/STAT 541

Course designed for the biomedical researcher. Topics include: descriptive statistics, hypothesis testing, estimation, confidence intervals, t-tests, chi-squared tests, analysis of variance, linear regression, correlation, nonparametric tests, survival analysis and odds ratio. Biomedical applications used for each topic.

INTRODUCTION TO STATISTICS FOR SCIENCE AND ENGINEERING

STAT 324

Descriptive statistics, probability concepts and distributions, random variables. Hypothesis tests and confidence intervals for one- and two-sample problems. Linear regression, model checking, and inference. Analysis of variance and basic ideas in experimental design. Utilizes the R programming language.

INTRODUCTION TO INDUSTRIAL STATISTICS

ISYE 210

Introduction to basic probability and statistical tools and methods from an industrial application perspective. Random variables and probability distributions; descriptive statistics; point estimates. Perform hypothesis testing, construct confidence intervals, and understand design of experiments in the context of motivating case studies. Regression and correlation analysis. Focus on applying statistical methods and tools to solve engineering problems. Use of Microsoft Excel to interpret and analyze data.

ENGINEERING APPLICATIONS OF STATISTICS

EPD 416

Provides knowledge and skills to apply statistics to many types of engineering problems. Focuses on developing statistically-based experimental techniques and tests for measures of validity, application of computer-based statistical tools, and approaches to distillation of data.

EXPERIMENTAL DESIGN AND ANALYSIS IN BIOTECHNOLOGY

ABT 720

Principles of descriptive and inferential statistics with applications in biotechnology including experimental design, quantitative data analysis, and bioinformatic evaluation of complex molecular and biological data sets.