This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.
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최근 조회 36,061회
유동적 마감일
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공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 5개 강좌 중 3번째 강좌:
초급 단계
완료하는 데 약 10시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 한국어, 독일어, 러시아어, 영어, 스페인어
귀하가 습득할 기술
StatisticsLinear RegressionR ProgrammingRegression Analysis
유동적 마감일
일정에 따라 마감일을 재설정합니다.
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 5개 강좌 중 3번째 강좌:
초급 단계
완료하는 데 약 10시간 필요
영어
자막: 아랍어, 프랑스어, 포르투갈어 (유럽), 이탈리아어, 베트남어, 한국어, 독일어, 러시아어, 영어, 스페인어
제공자:
듀크대학교
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 22분 필요
About Linear Regression and Modeling
This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Linear Regression and Modeling. Please take several minutes to browse them through. Thanks for joining us in this course!
완료하는 데 22분 필요
1개 동영상 (총 2분), 2 개의 읽기 자료
완료하는 데 2시간 필요
Linear Regression
In this week we’ll introduce linear regression. Many of you may be familiar with regression from reading the news, where graphs with straight lines are overlaid on scatterplots. Linear models can be used for prediction or to evaluate whether there is a linear relationship between two numerical variables.
완료하는 데 2시간 필요
8개 동영상 (총 47분), 3 개의 읽기 자료, 2 개의 테스트
완료하는 데 3시간 필요
More about Linear Regression
Welcome to week 2! In this week, we will look at outliers, inference in linear regression and variability partitioning. Please use this week to strengthen your understanding on linear regression. Don't forget to post your questions, concerns and suggestions in the discussion forum!
완료하는 데 3시간 필요
3개 동영상 (총 24분), 5 개의 읽기 자료, 3 개의 테스트
완료하는 데 3시간 필요
Multiple Regression
In this week, we’ll explore multiple regression, which allows us to model numerical response variables using multiple predictors (numerical and categorical). We will also cover inference for multiple linear regression, model selection, and model diagnostics. Hope you enjoy!
완료하는 데 3시간 필요
7개 동영상 (총 57분), 5 개의 읽기 자료, 3 개의 테스트
완료하는 데 1시간 필요
Final Project
In this week you will use the data set provided to complete and report on a data analysis question. Please read the background information, review the report template (downloaded from the link in Lesson Project Information), and then complete the peer review assignment.
완료하는 데 1시간 필요
1 개의 읽기 자료
검토
LINEAR REGRESSION AND MODELING 의 최상위 리뷰
TM 제공2020년 7월 21일
A great primer on linear regression with labs that help to establish understanding and a project that is focused enough not to be overwhelming, and allows the learner to play around with the concepts
PK 제공2017년 5월 23일
Very good course taught by Dr. Mine who is as always a very good teacher. The videos are very eloquent and easy to understand. Highly recommend it if you are looking for a basic refresher course.
DS 제공2017년 3월 29일
This course provides a very good introduction to basic linear regression, including simple multiple linear regression, model building and interpretation, model diagnostics, and application in R.
EB 제공2017년 2월 25일
Good, but a little "smaller" than the Inferential statistics course (which is very complete). I would have liked to also learn Logistics regression, which I now have to learn elsewhere.
Statistics with R 특화 과정 정보
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.
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