Intermediate Excel Statistics for Business Analytics

Resources for O'Reilly Online Learning course, "Intermediate Excel Statistics for Business Analytics"

Inferential statistics involves inferring parameters of a population based on the values of a sample. These tests can include comparing multiple populations for differences,comparing the same individual at different points in time, or predicting the value of one variable given another.

Join expert George Mount for a hands-on approach to conducting intermediate statistical inference using Microsoft Excel. By the end of this course, users will be able to organize, present, and draw valid conclusions from data, using inferential statistics for business impact.

What you'll learn — and how you can apply it By the end of this live, hands-on, online course, you’ll understand:

• The trade-off between Type I and Type II errors
• The relationship between correlation and causation
• How statistics and visualizations each play a part in effective quantitative analysis

And you’ll be able to:

• Make graphical representations of one or more variables
• Test for differences across multiple groups and at multiple points in time
• Model a causal relationship between two variables
• Make compelling business recommendations using inferential statistics

This training is for you because...

• You want to apply more rigorous methods to your business decision making.
• You’re an Excel user interested in learning more about data science.
• You’re a researcher or analyst looking to apply statistical methods to business.
• You can conduct basic statistical analysis in Excel and want to take your skills to the next level.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing.

Expected values and repeated measures (55 minutes)

Presentation: Chi-square test for independence—testing for a significant association between two categories; paired-sample t-test—testing for a significant difference between two points in time of the same individual; Wilcoxon signed-rank test—the advantages and disadvantages of parametric and nonparametric tests, working with nonnormal data Hands-on exercise: Clean a dataset and conduct analyses Q&A Break (5 minutes)

Working with multiple groups (55 minutes)

Presentation: Analysis of variance (ANOVA)—testing for a significant difference across more than two groups, post hoc tests and type I error; correlation—measuring the linear relation between two variables, correlations and visualizations Hands-on exercise: Continue visualizing and analyzing various statistical relationships Q&A Break (5 minutes)

Up and running with linear regression (60 minutes)

Presentation: From correlation to causation—the similarities and dissimilarities of correlation and regression; the terms and conditions of linear regression—checking assumptions, identifying regression “parts of speech”; regression interpretation and diagnostics—establishing significance, visualizing the results Hands-on exercise: Conduct an end-to-end linear regression analysis Q&A