This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good estimators, method of moments estimation, maximum likelihood estimation, and methods of constructing confidence intervals that will extend to more general settings.
課程信息
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第 2 門課程（共 3 門）
中級
Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.
完成時間大約為27 小時
英語（English）
字幕：英語（English）
您將學到的內容有
Identify characteristics of “good” estimators and be able to compare competing estimators.
Construct sound estimators using the techniques of maximum likelihood and method of moments estimation.
Construct and interpret confidence intervals for one and two population means, one and two population proportions, and a population variance.
可靈活調整截止日期
根據您的日程表重置截止日期。
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 2 門課程（共 3 門）
中級
Sequence in calculus up through Calculus II (preferably multivariate calculus) and some programming experience in R.
完成時間大約為27 小時
英語（English）
字幕：英語（English）
提供方
科罗拉多大学波德分校
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
立即開始攻讀碩士學位
此 課程 隸屬於 科罗拉多大学波德分校 提供的 100% 在線 Master of Science in Data Science。
如果您被錄取參加全部課程，您的課程將計入您的學位學習進程。
授課大綱 - 您將從這門課程中學到什麼
完成時間為 7 小時
Point Estimation
In this module you will learn how to estimate parameters from a large population based only on information from a small sample. You will learn about desirable properties that can be used to help you to differentiate between good and bad estimators. We will review the concepts of expectation, variance, and covariance, and you will be introduced to a formal, yet intuitive, method of estimation known as the "method of moments".
完成時間為 7 小時
10 個視頻 （總計 142 分鐘）, 10 個閱讀材料, 4 個測驗
完成時間為 5 小時
Maximum Likelihood Estimation
完成時間為 5 小時
5 個視頻 （總計 67 分鐘）, 5 個閱讀材料, 3 個測驗
完成時間為 5 小時
Large Sample Properties of Maximum Likelihood Estimators
In this module we will explore large sample properties of maximum likelihood estimators including asymptotic unbiasedness and asymptotic normality. We will learn how to compute the “Cramér–Rao lower bound” which gives us a benchmark for the smallest possible variance for an unbiased estimator.
完成時間為 5 小時
5 個視頻 （總計 100 分鐘）, 5 個閱讀材料, 2 個測驗
完成時間為 7 小時
Confidence Intervals Involving the Normal Distribution
完成時間為 7 小時
5 個視頻 （總計 99 分鐘）, 4 個閱讀材料, 3 個測驗
關於 Data Science Foundations: Statistical Inference 專項課程
This program is designed to provide the learner with a solid foundation in probability theory to prepare for the broader study of statistics. It will also introduce the learner to the fundamentals of statistics and statistical theory and will equip the learner with the skills required to perform fundamental statistical analysis of a data set in the R programming language.
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