Statistics and Data Analysis with Excel, Part 2

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Statistics and Data Analysis with Excel, Part 2

Name: Statistics and Data Analysis with Excel, Part 2
Rating: 4.6 (10 reviews)

Ce cours fait partie de Spécialisation "Statistics and Applied Data Analysis"

Instructeur : Charlie Nuttelman

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7 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

10 avis

niveau Intermédiaire

Expérience recommandée

2 semaines à compléter

à 10 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 : Sampling (Statistics)
Catégorie : Statistical Analysis
Catégorie : Probability Distribution
Catégorie : Probability & Statistics
Catégorie : Analysis
Catégorie : Statistical Hypothesis Testing
Catégorie : Statistical Methods
Catégorie : Excel Formulas
Catégorie : Data Analysis
Catégorie : Regression Analysis
Catégorie : Data Analysis Software
Catégorie : Statistical Modeling
Catégorie : Probability
Catégorie : Statistical Inference

Outils que vous découvrirez

Catégorie : Microsoft Excel
Catégorie : Statistical Software

Détails à connaître

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Enseigné en Anglais

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Ce cours fait partie de la Spécialisation "Statistics and Applied Data Analysis"

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Il y a 7 modules dans ce cours

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).

Statistical techniques are taught with the help of Microsoft Excel, which is an intuitive software package that has many built-in functions and tools for statistical analysis. This course is the second course out of three that comprise the specialization "Statistics and Applied Data Analysis." Course 3 ("Statistics and Data Analysis with R") focuses on statistical analysis in the statistical software package RStudio.

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 devoir1 sujet de discussion

5 vidéosTotal 31 minutes

Welcome to the Course!8 minutes
How the Course Works3 minutes
Standardizing and Z-Values, Part 111 minutes
Standardizing and Z-Values, Part 23 minutes
Inverse Normal Distribution Calculations6 minutes

6 lecturesTotal 21 minutes

Course Updates and Accessibility Support1 minute
The Importance of a Course Certificate and the Future of Higher Education10 minutes
What Version of Excel Do You Need for This Course?5 minutes
Do You Need to Review?1 minute
Percentage Points of the Standard Normal Distribution (Table)2 minutes
Week 2 Excel Files2 minutes

1 devoirTotal 2 minutes

Unlock Quiz for Week 2 Files2 minutes

1 sujet de discussionTotal 10 minutes

What About You?10 minutes

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 devoirs1 sujet de discussion

11 vidéosTotal 83 minutes

Introduction to Inferential Statistics7 minutes
Sampling Distribution vs. Population Distribution 9 minutes
The Central Limit Theorem5 minutes
Variance Known or Unknown?5 minutes
Confidence Interval on the Mean, Variance Known12 minutes
The T Distribution8 minutes
Confidence Interval on the Mean, Variance Unknown5 minutes
Using the CONFIDENCE.NORM and CONFIDENCE.T Functions in Excel 5 minutes
Prediction Interval on a Future Observation6 minutes
The Chi-Squared Distribution and Confidence Intervals on the Variance 11 minutes
Guided Workshop 2: Confidence Interval Calculator for Small Data Sets12 minutes

7 lecturesTotal 22 minutes

Week 2 Cheat Sheet2 minutes
Percentage Points of the T Distribution (Table)2 minutes
Excel Functions for the Standard Normal and T Distributions2 minutes
Percentage Points of the Chi-Squared Distribution (Table)2 minutes
Excel Functions for the Chi-Squared Distribution2 minutes
Guided Workshop 210 minutes
Week 3 Excel Files2 minutes

3 devoirsTotal 90 minutes

Guided Workshop 2 Submission30 minutes
Week 2 Graded Quiz30 minutes
Week 2 Practice Quiz30 minutes

1 sujet de discussionTotal 5 minutes

(OPTIONAL) Week 2 Discussion5 minutes

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 devoirs1 sujet de discussion

14 vidéosTotal 100 minutes

Introduction to Hypothesis Testing, Part 16 minutes
Introduction to Hypothesis Testing, Part 28 minutes
Hypothesis Tests on the Mean Using Confidence Intervals10 minutes
The Test Statistic Approach to Hypothesis Testing10 minutes
Using P-Values for Hypothesis Testing on the Mean, Part 16 minutes
Using P-Values for Hypothesis Testing on the Mean, Part 27 minutes
Type I and Type II Errors9 minutes
Example: Type II Error5 minutes
Power of the Test4 minutes
Choice of Sample Size and OC Curves7 minutes
Choice of Sample Size, Variance Unknown2 minutes
Hypothesis Tests on the Variance8 minutes
Hypothesis Tests on a Binomial Proportion8 minutes
Guided Workshop 3: Real-Time Power Calculator10 minutes

3 lecturesTotal 14 minutes

Week 3 Cheat Sheet2 minutes
Guided Workshop 310 minutes
Week 4 Excel Files2 minutes

3 devoirsTotal 90 minutes

Guided Workshop 3 Submission30 minutes
Week 3 Graded Quiz30 minutes
Week 3 Practice Quiz30 minutes

1 sujet de discussionTotal 5 minutes

(OPTIONAL) Week 3 Discussion5 minutes

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 devoirs1 sujet de discussion

8 vidéosTotal 67 minutes

Comparison of Means, Variance Known (Part 1)9 minutes
Comparison of Means, Variance Known (Part 2)7 minutes
Comparison of Means, Variance Unknown (Part 1)7 minutes
Comparison of Means, Variance Unknown (Part 2)4 minutes
Paired T-tests9 minutes
The F Distribution and Comparison of Variances9 minutes
Comparison of Proportions 5 minutes
Guided Workshop 4: Two-Sample T-Test Calculator17 minutes

6 lecturesTotal 28 minutes

Week 4 Cheat Sheet2 minutes
Comparison of Means Flowchart2 minutes
Excel Functions for the F Distribution10 minutes
Percentage Points of the F Distribution (Table)2 minutes
Guided Workshop 410 minutes
Week 5 Excel Files2 minutes

3 devoirsTotal 90 minutes

Guided Workshop 4 Submission30 minutes
Week 4 Graded Quiz30 minutes
Week 4 Practice Quiz30 minutes

1 sujet de discussionTotal 5 minutes

(OPTIONAL) Week 4 Discussion5 minutes

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 devoirs1 sujet de discussion

10 vidéosTotal 108 minutes

Linear Regression, Part 1: Simple Linear Models (Straight Line)9 minutes
Linear Regression, Part 2: General Linear Models12 minutes
Linear Regression, Part 3: Multilinear Regression10 minutes
Simple Linear Regression Using Least Squares Estimators12 minutes
Hypothesis Tests for Simple Linear Regression12 minutes
Confidence Intervals on Slope and Intercept12 minutes
Examples: Confidence Interval on the Slope9 minutes
Confidence Interval on the Mean Response11 minutes
Coefficient of Determination and Adjusted R-Squared8 minutes
Guided Workshop 5: Prediction Interval for a Future Observation14 minutes

3 lecturesTotal 14 minutes

Week 5 Cheat Sheet2 minutes
Guided Workshop 510 minutes
Week 6 Excel Files2 minutes

3 devoirsTotal 90 minutes

Guided Workshop 5 Submission30 minutes
Week 5 Graded Quiz30 minutes
Week 5 Practice Quiz30 minutes

1 sujet de discussionTotal 5 minutes

(OPTIONAL) Week 5 Discussion5 minutes

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 devoirs1 sujet de discussion

7 vidéosTotal 97 minutes

Matrix Approach to Multiple Linear Regression11 minutes
Statistical Properties of Least Squares Estimators12 minutes
Hypothesis Tests in Multiple Linear Regression, Part 110 minutes
Hypothesis Tests in Multiple Linear Regression, Part 210 minutes
Confidence Intervals in Multiple Linear Regression9 minutes
Introduction to Nonlinear Regression (Logistic Regression)14 minutes
Guided Workshop 6: Real-Time Multilinear Regression Calculator31 minutes

3 lecturesTotal 14 minutes

Week 6 Cheat Sheet2 minutes
Guided Workshop 610 minutes
Week 7 Excel Files2 minutes

3 devoirsTotal 90 minutes

Guided Workshop 6 Submission30 minutes
Week 6 Graded Quiz30 minutes
Week 6 Practice Quiz30 minutes

1 sujet de discussionTotal 5 minutes

(OPTIONAL) Week 6 Discussion5 minutes

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 devoirs1 sujet de discussion

4 vidéosTotal 48 minutes

Single-Factor ANOVA: Introduction and Terminology9 minutes
Single-Factor ANOVA: Partitioning the Sum of Squares and Creating the ANOVA Table11 minutes
Single-Factor ANOVA: Comparison of Means6 minutes
Guided Workshop 7: Two-Way Analysis of Variance22 minutes

2 lecturesTotal 12 minutes

Week 7 Cheat Sheet2 minutes
Guided Workshop 710 minutes

4 devoirsTotal 120 minutes

Guided Workshop 7 Submission30 minutes
Week 7 Graded Quiz30 minutes
Final Graded Quiz30 minutes
Week 7 Practice Quiz30 minutes

1 sujet de discussionTotal 5 minutes

(OPTIONAL) Week 7 Discussion5 minutes

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Instructeur

Charlie Nuttelman

University of Colorado Boulder

10 Cours487 555 apprenants

Offert par

University of Colorado Boulder

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Affichage de 3 sur 10

Révisé le 3 nov. 2025

A really great blend of some theory but a lot of practical experience using statistics in Excel. The course leader presents the material very clearly.

Révisé le 12 sept. 2024

The Specialization is a very thorough learning about Statistics with many examples for us to understand the principles. Some modules are hard but fun.

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Foire Aux Questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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