开始时间: 04/22/2022 持续时间: Unknown
|
所在平台: CourseraArchive 课程类别: 数学 大学或机构: University of Zurich（苏黎世大学） 授课老师： Marco Steenbergen |
课程主页: https://www.coursera.org/course/statistics101
课程评论：没有评论
Statistics is the lingua franca of modern science, including the social sciences. It is also of ever greater importance in daily life, as data of all sorts are now ubiquitous. Statistical literacy is hence of great value, both for academic purposes and for our daily routines. This course offers a solid foundation in statistical reasoning and its uses in the quantitative social sciences.
Learning statistics can be a daunting experience. There is a plethora of statistical concepts to master and many of them come with a hefty dose of mathematical notation. The goal of the present course is to develop a clear path through the conceptual forest and to explain each concept both in its narrow meaning and as a part of the larger enterprise of statistical reasoning. Mathematical skills are not taken for granted; instead, we shall review the necessary mathematical tools so that you will not get stuck on this aspect.
The field of statistics is sometimes divided into descriptive and inferential statistics, with probability theory forming a bridge between the two. In this course, we start out descriptively, by considering different ways in which we can learn from data. We then delve into the subject of probability theory, to end with a discussion of statistical inference. The emphasis in this part is on learning how to draw conclusions about populations with the help of data from a sample.
By the end of this course, you should have a good feeling for descriptive statistics, statistical inference, and probability theory. You should also understand the interplay of these elements in the broader enterprise of statistical reasoning. And you should feel more comfortable reading about statistics and using them in your own work.
MODULE I: DESCRIPTIVE STATISTICS
Week 1: Understanding the properties of a single variable through visualization
Week 2: Understanding the properties of a single variable through summary statistics
Week 3: Understanding associations between variables
MODULE II: PROBABILITY THEORY
Week 4: Understanding and computing with probabilities
Week 5: Random variables and distributions
Week 6: Commonly used statistical distributions
MODULE III: INFERENTIAL STATISTICS
Week 7: Understanding sampling
Week 8: A primer of estimation theory
Week 9: The theory of hypothesis testing
Week 10: Commonly used statistical tests
This course exposes students to the logic of statistical reasoning and its application in the quantitative social sciences. It is meant as a thorough but accessible introduction to the topics of descriptive statistics, probability theory, and statistical inference with hands-on exercises.
