Confidence Trickster: How to know when you're right

Track: Data Analytics Symposium

Session Number: 2055
Date: Thu, Aug 1st, 2019
Time: 3:10 PM - 3:30 PM
Room: Grand Saguaro East

Description:

Learning about data analysis comes along with a tricky Catch-22: the smarter we get about data analysis and statistical methods, the less confident we become in knowing when we have made the correct conclusions about our data. To make a long story short--we become our own confidence tricksters. In this lecture, Dr. Duke will discuss ways we can be confident that our analysis is correct, by using the statistical concepts of significance and confidence to both confirm the success of our analysis and to include probability intervals for success. Dr. Duke will also explore how to summarize and visualize data presentations in ways that establish the credibility of your analysis, and establish you as a realistic and important part of your organization's planmaking team.
Session Type: DAS Case Study (20min)

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 5: Visualization/Reporting Techniques and Competencies
Tertiary Competency: DA:Competency 6: Strategic Management & Communication
Intended Audience Level: Level I, Level II
Recommended Prerequisites: None
Learning Objective #1: Attendees will learn the concepts of significance with respect to prospect data variables, and confidence with respect to statistical modeling methods.
Learning Objective #2: Attendees will also learn how to use these concepts to more confidently present data-driven results to others in a development office.
Shop Size: All Shop Sizes
Session Type: DAS Case Study (20min)

Primary Competency: DA:Competency 4: Statistical Techniques and Competencies
Secondary Competency: DA:Competency 5: Visualization/Reporting Techniques and Competencies
Tertiary Competency: DA:Competency 6: Strategic Management & Communication
Intended Audience Level: Level I, Level II
Recommended Prerequisites: None
Learning Objective #1: Attendees will learn the concepts of significance with respect to prospect data variables, and confidence with respect to statistical modeling methods.
Learning Objective #2: Attendees will also learn how to use these concepts to more confidently present data-driven results to others in a development office.
Shop Size: All Shop Sizes