Statistics and Data Analysis with Excel, Part 2

Statistics and Data Analysis with Excel, Part 2

This course is part of Statistics and Applied Data Analysis Specialization

Instructor: Charlie Nuttelman

Access provided by Samsung Research, Bangalore

7 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

7 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

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.

Skills you'll gain

Tools you'll learn

Microsoft Excel

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

20 assignments

Taught in English

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This course is part of the Statistics and Applied Data Analysis Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 7 modules in this course

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.

What's included

5 videos6 readings1 assignment1 discussion prompt

5 videos Total 31 minutes

Welcome to the Course! 8 minutes
How the Course Works 3 minutes
Standardizing and Z-Values, Part 1 11 minutes
Standardizing and Z-Values, Part 2 3 minutes
Inverse Normal Distribution Calculations 6 minutes

6 readings Total 21 minutes

Course Updates and Accessibility Support 1 minute
The Importance of a Course Certificate and the Future of Higher Education 10 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 Files 2 minutes

1 assignment Total 2 minutes

Unlock Quiz for Week 2 Files 2 minutes

1 discussion prompt Total 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.

What's included

11 videos7 readings3 assignments1 discussion prompt

11 videos Total 83 minutes

Introduction to Inferential Statistics 7 minutes
Sampling Distribution vs. Population Distribution 9 minutes
The Central Limit Theorem 5 minutes
Variance Known or Unknown? 5 minutes
Confidence Interval on the Mean, Variance Known 12 minutes
The T Distribution 8 minutes
Confidence Interval on the Mean, Variance Unknown 5 minutes
Using the CONFIDENCE.NORM and CONFIDENCE.T Functions in Excel 5 minutes
Prediction Interval on a Future Observation 6 minutes
The Chi-Squared Distribution and Confidence Intervals on the Variance 11 minutes
Guided Workshop 2: Confidence Interval Calculator for Small Data Sets 12 minutes

7 readings Total 22 minutes

Week 2 Cheat Sheet 2 minutes
Percentage Points of the T Distribution (Table) 2 minutes
Excel Functions for the Standard Normal and T Distributions 2 minutes
Percentage Points of the Chi-Squared Distribution (Table) 2 minutes
Excel Functions for the Chi-Squared Distribution 2 minutes
Guided Workshop 2 10 minutes
Week 3 Excel Files 2 minutes

3 assignments Total 90 minutes

Guided Workshop 2 Submission 30 minutes
Week 2 Graded Quiz 30 minutes
Week 2 Practice Quiz 30 minutes

1 discussion prompt Total 5 minutes

(OPTIONAL) Week 2 Discussion 5 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.

What's included

14 videos3 readings3 assignments1 discussion prompt

14 videos Total 100 minutes

Introduction to Hypothesis Testing, Part 1 6 minutes
Introduction to Hypothesis Testing, Part 2 8 minutes
Hypothesis Tests on the Mean Using Confidence Intervals 10 minutes
The Test Statistic Approach to Hypothesis Testing 10 minutes
Using P-Values for Hypothesis Testing on the Mean, Part 1 6 minutes
Using P-Values for Hypothesis Testing on the Mean, Part 2 7 minutes
Type I and Type II Errors 9 minutes
Example: Type II Error 5 minutes
Power of the Test 4 minutes
Choice of Sample Size and OC Curves 7 minutes
Choice of Sample Size, Variance Unknown 2 minutes
Hypothesis Tests on the Variance 8 minutes
Hypothesis Tests on a Binomial Proportion 8 minutes
Guided Workshop 3: Real-Time Power Calculator 10 minutes

3 readings Total 14 minutes

Week 3 Cheat Sheet 2 minutes
Guided Workshop 3 10 minutes
Week 4 Excel Files 2 minutes

3 assignments Total 90 minutes

Guided Workshop 3 Submission 30 minutes
Week 3 Graded Quiz 30 minutes
Week 3 Practice Quiz 30 minutes

1 discussion prompt Total 5 minutes

(OPTIONAL) Week 3 Discussion 5 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.

What's included

8 videos6 readings3 assignments1 discussion prompt

8 videos Total 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-tests 9 minutes
The F Distribution and Comparison of Variances 9 minutes
Comparison of Proportions 5 minutes
Guided Workshop 4: Two-Sample T-Test Calculator 17 minutes

6 readings Total 28 minutes

Week 4 Cheat Sheet 2 minutes
Comparison of Means Flowchart 2 minutes
Excel Functions for the F Distribution 10 minutes
Percentage Points of the F Distribution (Table) 2 minutes
Guided Workshop 4 10 minutes
Week 5 Excel Files 2 minutes

3 assignments Total 90 minutes

Guided Workshop 4 Submission 30 minutes
Week 4 Graded Quiz 30 minutes
Week 4 Practice Quiz 30 minutes

1 discussion prompt Total 5 minutes

(OPTIONAL) Week 4 Discussion 5 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.

What's included

10 videos3 readings3 assignments1 discussion prompt

10 videos Total 108 minutes

Linear Regression, Part 1: Simple Linear Models (Straight Line) 9 minutes
Linear Regression, Part 2: General Linear Models 12 minutes
Linear Regression, Part 3: Multilinear Regression 10 minutes
Simple Linear Regression Using Least Squares Estimators 12 minutes
Hypothesis Tests for Simple Linear Regression 12 minutes
Confidence Intervals on Slope and Intercept 12 minutes
Examples: Confidence Interval on the Slope 9 minutes
Confidence Interval on the Mean Response 11 minutes
Coefficient of Determination and Adjusted R-Squared 8 minutes
Guided Workshop 5: Prediction Interval for a Future Observation 14 minutes

3 readings Total 14 minutes

Week 5 Cheat Sheet 2 minutes
Guided Workshop 5 10 minutes
Week 6 Excel Files 2 minutes

3 assignments Total 90 minutes

Guided Workshop 5 Submission 30 minutes
Week 5 Graded Quiz 30 minutes
Week 5 Practice Quiz 30 minutes

1 discussion prompt Total 5 minutes

(OPTIONAL) Week 5 Discussion 5 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).

What's included

7 videos3 readings3 assignments1 discussion prompt

7 videos Total 97 minutes

Matrix Approach to Multiple Linear Regression 11 minutes
Statistical Properties of Least Squares Estimators 12 minutes
Hypothesis Tests in Multiple Linear Regression, Part 1 10 minutes
Hypothesis Tests in Multiple Linear Regression, Part 2 10 minutes
Confidence Intervals in Multiple Linear Regression 9 minutes
Introduction to Nonlinear Regression (Logistic Regression) 14 minutes
Guided Workshop 6: Real-Time Multilinear Regression Calculator 31 minutes

3 readings Total 14 minutes

Week 6 Cheat Sheet 2 minutes
Guided Workshop 6 10 minutes
Week 7 Excel Files 2 minutes

3 assignments Total 90 minutes

Guided Workshop 6 Submission 30 minutes
Week 6 Graded Quiz 30 minutes
Week 6 Practice Quiz 30 minutes

1 discussion prompt Total 5 minutes

(OPTIONAL) Week 6 Discussion 5 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.

What's included

4 videos2 readings4 assignments1 discussion prompt

4 videos Total 48 minutes

Single-Factor ANOVA: Introduction and Terminology 9 minutes
Single-Factor ANOVA: Partitioning the Sum of Squares and Creating the ANOVA Table 11 minutes
Single-Factor ANOVA: Comparison of Means 6 minutes
Guided Workshop 7: Two-Way Analysis of Variance 22 minutes