Scott Crawford, Ph.D.Stat 692 - Consulting
Click here for the SyllabusChapter 0: Consulting
Video 1.1: About the class and meVideo 1.2: Data Science and Stat careers
Video 1.3: Skills focus for this course
Chapter 1: Job applications
Video 2.1: Looking for jobsVideo 2.2: Filling out the application
Video 2.3: Emotional Preparation
Video 2.4: The interview
Video 2.5: Accepting the offer
Chapter 2: Before you meet
Video 3.1: Mental and Time preparationVideo 3.2: Setting the expectations
Video 3.3: Things that will change the analysis
Video 3.4: Company Dynamics
Video 3.5: Planning our consulting project
Chapter 3: Client meetings
Video 4.1: Keep it simple sillyVideo 4.2: Respect for the Client
Video 4.3: Nonverbal Communication
Video 4.4: Client Meetings
Chapter 4: When things go wrong
Video 5.1: Avoiding problems in the first placeVideo 5.2: Resolving issues as a team
Video 5.3: Negotiation
Video 5.4: Understanding the client
Chapter 5: Ethics
Video 6.1: Why unethical research happensVideo 6.2: Ethics as a statistical consultant with data
Video 6.3: Ethical relationships with clients and subjects
Video 6.4: Ethics to other researchers
Chapter 6: Before data
Video 7.1: Sample sizes and lurking variablesVideo 7.2: Observational Studies
Video 7.3: Experiments and Interactions
Video 7.4: Blocks
Chapter 7: After data
Video 8.1: Missing DataVideo 8.2: Outliers and Errors
Video 8.3: Residuals, Excel, SQL
Video 8.4: Big Data
Video 8.5: R Tricks
Chapter 8: Starting analysis
Video 9.1: Induction for point estimatesVideo 9.2: Bias vs Variance
Video 9.3: Four lies we tell intro students
Video 9.4: Deciding on the model metrics
Video 9.5: Picking variables and Rubric
Chapter 9: Choices
Video 10.1: Does it matter - which programVideo 10.2: Basic Intro level choices
Video 10.3: Non=parametrics and sums of squares
Video 10.4: The philosophies of Bayes vs Frequentist
Video 10.5: Bayesian Statistics
Chapter 10: Checking
Video 11.1: Checking data and residualsVideo 11.2: More about residuals
Video 11.3: Resampling methods
Chapter 11: Wow factor
Video 12.1: Why do we need a wow factor?Video 12.2: Tidyverse Package in R
Video 12.3: Scientific and Information Visualization
Video 12.4: Analytical Visualization
Video 12.5: Don't go from wow to whoa
Chapter 12: Finish
Video 13.1: Tone and size of the reportVideo 13.2: Formatting, intro, data, and model
Video 13.3: Validation, complexity, graphs, output, conclusion
Video 13.4: The presentation