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LinkedIn Learning

Excel Statistics Essential Training: 2

via LinkedIn Learning

Overview

Learn more statistics fundamentals. Find out how to perform ANOVA, regression, and correlation testing and run simulations in Microsoft Excel.

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.

Syllabus

Introduction
  • Continuing your data analysis journey
1. Excel Statistics Fundamentals
  • Using Excel statistical functions
  • Using the Analysis Toolpak
  • Using statistical charts
  • Using 3D maps
  • Using the Ideas tool
2. Visualizing Sampling Distributions
  • Simulating the central limit theorem
  • Visualizing the standard normal and t
  • Visualizing F and chi-square
3. ANOVA: A Closer Look
  • Analyzing between groups ANOVA
  • Performing simple comparisons
  • Performing complex comparisons
  • Performing repeated measures ANOVA
  • Trend analysis
4. ANOVA: A Complex Look
  • Performing two-way ANOVA
  • Making comparisons after two-way ANOVA
5. Linear Regression: A Closer Look
  • Visualizing scatter plot and regression line
  • Analyzing the regression line
6. Multiple Regression
  • Performing multiple regression
7. Nonlinear Regression
  • Defining natural logs and exponents
  • Performing exponential regression analysis
  • Performing logarithmic regression analysis
  • Performing a power regression analysis
  • Performing polynomial regression analysis
  • Performing logistic regression
8. Time Series
  • Forecasting and predicting
9. Advanced Correlation
  • Performing correlation
  • Comparing two correlation coefficients
  • Performing multiple correlations
  • Performing a partial correlation
10. Frequency Hypothesis Testing
  • Testing the independence of two variables
  • Testing goodness of fit
11. Simulation
  • Performing Monte Carlo simulation
  • Performing business simulations
Conclusion
  • Next steps

Taught by

Joseph Schmuller

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