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来源:www.coursera.org
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10个序列
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等级:入门
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数据分析
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语言:英语
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640分
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80小时总数
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This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
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课程大纲
Week 1: Unit 1 - Introduction to data
- Part 1 – Designing studies
- Part 2 – Exploratory data analysis
- Part 3 – Introduction to inference via simulation
- Part 1 – Defining probability
- Part 2 – Conditional probability
- Part 3 – Normal distribution
- Part 4 – Binomial distribution
- Part 1 – Variability in estimates and the Central Limit Theorem
- Part 2 – Confidence intervals
- Part 3 – Hypothesis tests
- Part 4 – Inference for other estimators
- Part 5 - Decision errors, significance, and confidence
- Part 1 – t-inference
- Part 2 – Power
- Part 3 – Comparing three or more means (ANOVA)
- Part 4 – Simulation based inference for means
- Part 1 – Single proportion
- Part 2 – Comparing two proportions
- Part 3 – Inference for proportions via simulation
- Part 4 – Comparing three or more proportions (Chi-square)
- Part 1 – Relationship between two numerical variables
- Part 2 – Linear regression with a single predictor
- Part 3 – Outliers in linear regression
- Part 4 – Inference for linear regression
- Part 1 – Regression with multiple predictors
- Part 2 – Inference for multiple linear regression
- Part 3 – Model selection
- Part 4 – Model diagnostics
- Bayesian vs. frequentist inference
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教师
- Mine Çetinkaya-Rundel - Department of Statistical Science
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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.
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Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。
Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。
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Am truely impress with content, Platform and animation this site provides to learners. Looking forward to enrich my data analysis skills
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Am truely impress with content, Platform and animation this site provides to learners. Looking forward to enrich my data analysis skills