Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.
约翰霍普金斯大学課程信息
學生職業成果
43%
40%
14%
您將獲得的技能
學生職業成果
43%
40%
14%
提供方
约翰霍普金斯大学
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
教學大綱 - 您將從這門課程中學到什麼
Week 1: Probability & Expected Values
This week, we'll focus on the fundamentals including probability, random variables, expectations and more.
Week 2: Variability, Distribution, & Asymptotics
We're going to tackle variability, distributions, limits, and confidence intervals.
Week: Intervals, Testing, & Pvalues
We will be taking a look at intervals, testing, and pvalues in this lesson.
Week 4: Power, Bootstrapping, & Permutation Tests
We will begin looking into power, bootstrapping, and permutation tests.
審閱
來自统计推断的熱門評論
Course is compressed with lots of statistical concepts. Which is very good as most must know concepts are imparted. Lots of extra reading is required to gain all insights. Very good motivating start .
The strategy for model selection in multivariate environment should have been explained with an example. This will make the model selection process, interaction and its interpretation more clear.
I found this course really good introduction to statistical inference. I did find it quite challenging but I can go away from this course having a greater understanding of Statistical Inference
Very good course for the beginners who want to learn about statistical inference, R programming. A good explanation with the helpful R exercises makes us understand the concepts very easily.
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