This course is meant to be a direct continuation of "Statistics and Data Analysis with Excel, Part 1." Therefore, it is not recommended to take Part 2 unless you've also taken Part 1. Building on the topics learned in Part 1 of the course (probability, probability mass and density functions, the normal and standard normal distributions), this course dives into a more applied side of statistics. Topics in Part 2 include sampling distributions; one-sample hypothesis tests on the mean, variance, and binomial proportion; two-sample hypothesis tests (comparison of means, variances, and binomial proportions of samples drawn from two populations); simple (straight-line) regression; multilinear regression; and analysis of variance (ANOVA).
Statistics and Data Analysis with Excel, Part 2
Statistics and Data Analysis with Excel, Part 2
Enseigné en Anglais
niveau Intermédiaire
Expérience recommandée
21 heures pour terminer
3 semaines à 7 heures par semaine
Planning flexible
Apprenez à votre propre rythme
Ce que vous apprendrez
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.
Compétences que vous acquerrez
- Catégorie : Simple Linear Regression
- Catégorie : Microsoft Excel
- Catégorie : Linear Regression
- Catégorie : Analysis Of Variance (ANOVA)
- Catégorie : Statistical Hypothesis Testing
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Il y a 7 modules dans ce cours
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.
Inclus
5 vidéos6 lectures1 quiz1 sujet de discussion
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.
Inclus
11 vidéos7 lectures3 quizzes1 sujet de discussion
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.
Inclus
14 vidéos3 lectures3 quizzes1 sujet de discussion
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.
Inclus
8 vidéos6 lectures3 quizzes1 sujet de discussion
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.
Inclus
10 vidéos3 lectures3 quizzes1 sujet de discussion
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).
Inclus
7 vidéos3 lectures3 quizzes1 sujet de discussion
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.
Inclus
4 vidéos2 lectures4 quizzes1 sujet de discussion
Instructeur
Offert par
Recommandé si vous êtes intéressé(e) par Data Analysis
University of Colorado Boulder
Rice University
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