Data Literacy: Busting Myths of Big Data

Dr. Nairanjana Dasgupta, Boeing Science/Math Education Distinguished Professor in Mathematics and Statistics

In this workshop we will focus on learning about the what, when, how and whys of data. Data is pervasive these days and like it or not we have to use data to make decisions or others will make them for us. In this workshop we will start from the basics and talk about types of data and we can say and cannot say about the different types of data. Some of the topics we will cover are given below. We will keep it flexible and cover topics that attendees are interested in from the list below. This is not meant to replace any of your Stats classes, more of a philosophical overview of making data based decisions.

Types of Data. Why we collect data?
Population versus Sample
Experiments, observational studies
Exploratory studies versus confirmatory studies
The Idea of inference
Distinction: Uni-variate, Bi-variate, Multi-variate, multiple
Graphical Summary of data
Numerical summary of data
From center to one sample tests
Going from population to sample
Testing and Confidence Intervals
Errors in testing
Type I and Type II: which one is worse
Power
Margin of error and power
Sample size from power and vice versa
Type of design and power
Understanding effect size
Statistical significance
P-value – good, bad or misused
Overview