Excel Statistics Essential Training: 2 (2019)

Course details

Data isn’t valuable until you put it to good use. Statistics transforms data into meaningful information, enabling organizations to make better decisions and predictions. That’s why statistics—collecting, analyzing, and presenting data—is a valuable skill for anyone in business or academia. This course, part two of a series, continues your training on the fundamentals of descriptive and inferential statistics. Dr. Joseph Schmuller teaches you how to use the tools in Microsoft Excel—statistical functions, 3D maps and charts, the Ideas tool, and the Analysis Toolpak add-on—to carry out more sophisticated statistical analysis. First, learn to visualize sampling distributions. Next, test differences with analysis of variance (ANOVA). Then, find out how to use linear, multiple, and nonlinear regression to analyze relationships between variables and to make predictions. Joe also shows how to perform advanced correlations, test hypotheses about frequencies, and create and run simulations. Once you complete both courses, you should have the foundational knowledge to ace your next exam or interview and perform statistical analyses in the workplace.

Learning objectives
Review the benefits of installing the Data Analysis Toolpak add-on.
Describe the effect of changing degrees of freedom on a chi-square distribution visualization.
Determine when to use a complex comparison given a scenario.
Identify the process involved when using a two-way ANOVA.
Explain the analysis when you perform an exponential regression.
Define the way in which expected values are calculated.

Concepts

0. Introduction

01 - Continuing your data analysis journey

1. Excel Statistics Fundamentals

02 - Using Excel statistical functions
03 - Using the Analysis Toolpak
04 - Using statistical charts
05 - Using 3D maps
06 - Using the Ideas tool

2. Visualizing Sampling Distributions

07 - Simulating the central limit theorem
08 - Visualizing the standard normal and t
09 - Visualizing F and chi-square

3. ANOVA - A Closer Look

10 - Analyzing between groups ANOVA
11 - Performing simple comparisons
12 - Performing complex comparisons
13 - Performing repeated measures ANOVA
14 - Trend analysis

4. ANOVA - A Complex Look

15 - Performing two-way ANOVA
16 - Making comparisons after two-way ANOVA

5. Linear Regression - A Closer Look

17 - Visualizing scatter plot and regression line
18 - Analyzing the regression line

6. Multiple Regression

19 - Performing multiple regression

7. Nonlinear Regression

20 - Defining natural logs and exponents
21 - Performing exponential regression analysis
22 - Performing logarithmic regression analysis
23 - Performing a power regression analysis
24 - Performing polynomial regression analysis
25 - Performing logistic regression

8. Time Series

26 - Forecasting and predicting

9. Advanced Correlation

27 - Performing correlation
28 - Comparing two correlation coefficients
29 - Performing multiple correlations
30 - Performing a partial correlation

10. Frequency Hypothesis Testing

31 - Testing the independence of two variables
32 - Testing goodness of fit

11. Simulation

33 - Performing Monte Carlo simulation
34 - Performing business simulations

Conclusion

35 - Next steps