In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed. Throughout the course, you will share your progress with others to gain valuable feedback and provide insight to other learners about their work.
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최근 조회 10,738회
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33%
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지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 5개 강좌 중 2번째 강좌:
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완료하는 데 약 10시간 필요
영어
자막: 영어
귀하가 습득할 기술
Chi-Squared (Chi-2) DistributionData AnalysisStatistical Hypothesis TestingAnalysis Of Variance (ANOVA)
학습자 경력 결과
29%
가 이 강좌를 수료한 후 새로운 커리어를 시작함
33%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
17%
가 급여 인상 또는 승진 성취
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 5개 강좌 중 2번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 10시간 필요
영어
자막: 영어
제공자:
웨슬리언 대학교
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강의 계획 - 이 강좌에서 배울 내용
완료하는 데 4시간 필요
Hypothesis Testing and ANOVA
This session starts where the Data Management and Visualization course left off. Now that you have selected a data set and research question, managed your variables of interest and visualized their relationship graphically, we are ready to test those relationships statistically. The first group of videos describe the process of hypothesis testing which you will use throughout this course to test relationships between different kinds of variables (quantitative and categorical). Next, we show you how to test hypotheses in the context of Analysis of Variance (when you have one quantitative variable and one categorical variable). Your task will be to write a program that manages any additional variables you may need and runs and interprets an Analysis of Variance test. Note that if your research question does not include one quantitative variable, you can use one from your data set just to get some practice with the tool. If your research question does not include a categorical variable, you can categorize one that is quantitative.
완료하는 데 4시간 필요
14개 동영상 (총 79분), 11 개의 읽기 자료, 1 개의 테스트
14개의 동영상
Lesson 2 - From sample to population5m
Lesson 3 - Steps in hypothesis testing7m
Lesson 4 - What is a p value?5m
Lesson 5 - How to choose a statistical test1m
Lesson 6 - Ideas behind ANOVA9m
SAS Lesson 7 - ANOVA: Explanatory variable with 2 levels6m
SAS Lesson 8 - ANOVA: Explanatory variables with more than 2 levels2m
SAS Lesson 9 - Post hoc tests for ANOVA5m
SAS Lesson 10 - ANOVA summary2m
Python Lesson 7 - ANOVA: Explanatory variables with two levels8m
Python Lesson 8 - ANOVA: Explanatory variables with more than 2 levels3m
Python Lesson 9 - Post hoc tests for ANOVA5m
Python Lesson 10 - ANOVA Summary3m
11개의 읽기 자료
Choosing SAS or Python10m
Getting Started with SAS10m
Getting Started with Python10m
Course Codebooks10m
Course Data Sets10m
Uploading Your Own Data to SAS10m
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Getting set up for the assignments10m
Tumblr Instructions10m
Example: Running an analysis of variance10m
완료하는 데 2시간 필요
Chi Square Test of Independence
This session shows you how to test hypotheses in the context of a Chi-Square Test of Independence (when you have two categorical variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a Chi-Square Test of Independence. Note that if your research question only includes quantitative variables, you can categorize those just to get some practice with the tool.
완료하는 데 2시간 필요
7개 동영상 (총 48분), 3 개의 읽기 자료, 1 개의 테스트
7개의 동영상
SAS Lesson 2 - Chi Square Test of independence in practice5m
SAS Lesson 3 - Post hoc tests for Chi Square tests of independence10m
SAS Lesson 4 - Chi Square summary1m
Python Lesson 2 - Chi Square test of independence in practice8m
Python Lesson 3 - Post hoc tests for Chi Square tests of independence8m
Python Lesson 4 - Chi Square summary1m
3개의 읽기 자료
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
Example: Running a Chi-Square Test of Independence10m
완료하는 데 2시간 필요
Pearson Correlation
This session shows you how to test hypotheses in the context of a Pearson Correlation (when you have two quantitative variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a correlation coefficient. Note that if your research question only includes categorical variables, you can choose other variables from your data set just to get some practice with the tool.
완료하는 데 2시간 필요
4개 동영상 (총 18분), 2 개의 읽기 자료, 1 개의 테스트
4개의 동영상
Lesson 2 - Correlation Example3m
SAS Lesson 3 - Calculating Correlation4m
Python Lesson 3 - Calculating Correlation4m
2개의 읽기 자료
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
완료하는 데 2시간 필요
Exploring Statistical Interactions
In this session, we will discuss the basic concept of statistical interaction (also known as moderation). In statistics, moderation occurs when the relationship between two variables depends on a third variable. The effect of a moderating variable is often characterized statistically as an interaction; that is, a third variable that affects the direction and/or strength of the relation between your explanatory (X) and response (Y) variable. Your task will be to test your own research question in the context of one or more potential moderating variables.
완료하는 데 2시간 필요
9개 동영상 (총 51분), 2 개의 읽기 자료, 1 개의 테스트
9개의 동영상
SAS Lesson 2 - Testing moderation in the context of ANOVA4m
SAS Lesson 3 - Testing moderation in the context of chi square6m
SAS Lesson 4 - Testing moderation in the context of correlation4m
Python Lesson 1 - Defining moderation, a.k.a. statistical interaction4m
Python Lesson 2 - Testing moderation in the context of ANOVA4m
Python Lesson 3 - Testing moderation in the context of Chi-Square4m
Python Lesson 4 - Testing moderation in the context of correlation4m
A Question of Causation (Used with Permission from Annenberg Learner)14m
2개의 읽기 자료
SAS Program Code for Video Examples10m
Python Program Code for Video Examples10m
검토
DATA ANALYSIS TOOLS의 최상위 리뷰
DL 제공2015년 12월 19일
Again, with no formal SAS training and minimal statistics background. I found taking the first course and then this course - week after week my knowledge grew in a consistent and organized fashion.
AS 제공2017년 2월 9일
This was good module. It covers the basics of inferential statistical techniques along with its application using SAS/Python. I would definitely recommend to take up if you are a beginner.
AM 제공2015년 12월 2일
Very good for beginners. concept explanation as well as coding were great. doesn't take too long to finish. I enrolled regression modeling course by Wesleyan and waiting to start.
GR 제공2017년 10월 4일
Just love this whole specialisation! videos are great, lessons are great... it's just a great course! highly recommended to anyone looking to dive into the field of data analysis!
Data Analysis and Interpretation 특화 과정 정보
Learn SAS or Python programming, expand your knowledge of analytical methods and applications, and conduct original research to inform complex decisions.
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