University of Colorado Boulder
Statistics and Data Analysis with Excel, Part 2
University of Colorado Boulder

Statistics and Data Analysis with Excel, Part 2

Charlie Nuttelman

位教师:Charlie Nuttelman

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2 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度

您将学到什么

  • Perform one- and two-sample hypothesis tests on the mean and variance to make statistical decisions.

  • Create and interpret predictive regression models (linear and multiple) from experimental data.

  • Use ANOVA (analysis of variance) to compare means of multiple samples.

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作业

20 项作业

授课语言:英语(English)

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积累特定领域的专业知识

本课程是 Statistics and Applied Data Analysis 专项课程 专项课程的一部分
在注册此课程时,您还会同时注册此专项课程。
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  • 获得对主题或工具的基础理解
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  • 获得可共享的职业证书

该课程共有7个模块

Week 1 of the course is an introduction to Part 2 of "Statistics and Data Analysis with Excel." You will have several short, orientation-type reading assignments and you will have the opportunity to review some important concepts from Part 1 of the course. Finally, you'll be introduced to some of the main concepts and goals of the course.

涵盖的内容

5个视频5篇阅读材料1个作业1个讨论话题

In Week 2 of the course, you will learn all about sampling distributions and how they are different from population distributions, which you learned about in Part 1 of the course. You will also learn about the "variance known" and "variance unknown" cases and the differences between them. You'll learn all about the T distribution and how to create confidence intervals on the population mean when variance is known and unknown. Finally, you will learn about the chi-squared distribution and how to create confidence intervals on the population variance.

涵盖的内容

11个视频7篇阅读材料3个作业1个讨论话题

Week 3 will introduce you to hypothesis testing. You will perform hypothesis tests on single-sample parameters (mean and variance). You will then learn about Type I and Type II errors, how to calculate beta and power, and how to determine sample size for a specified power of the test. Finally, you will learn how to perform hypothesis tests on a binomial proportion.

涵盖的内容

14个视频3篇阅读材料3个作业1个讨论话题

Week 4 is all about hypothesis tests related to comparision of means, variances, and binomial proportions of two populations. You will also learn how to perform paired T-tests and you will learn how to use the F distribution.

涵盖的内容

8个视频6篇阅读材料3个作业1个讨论话题

Week 5 introduces you to linear regression models. You will learn how to create simple linear regression models, perform hypothesis tests on the slope and intercept, and calculate the coefficient of determination and adjusted R-squared value. You will also learn how to use Excel's Regression tool to create linear regression models.

涵盖的内容

10个视频3篇阅读材料3个作业1个讨论话题

Building off of concepts you learned in Week 5 of the course, Week 6 will introduce you to multiple linear regression models. You will learn how to perform hypothesis tests on model parameters and how to create confidence and prediction intervals. Finally, you will be introduced to nonlinear regression (logistic regression).

涵盖的内容

7个视频3篇阅读材料3个作业1个讨论话题

In Week 7, you will learn the basics of one-way and two-way analysis of variance (ANOVA). You will learn how to do this "by hand" and also using a built-in tool in Excel.

涵盖的内容

4个视频2篇阅读材料4个作业1个讨论话题

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位教师

Charlie Nuttelman
University of Colorado Boulder
10 门课程464,649 名学生

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