Statistics = Science(Data) + Art(Intuition)
Data Science Workshop
Upcoming and previous talks and workshops
2023-08-08: Programming for Data Science, JSM 2023
2022-10-13: What Merchants Need in North America, Shopify Unite 2022,
YouTube
2022-06-13: Data Science in Practice, 2022 Quality and Productivity Research conference
2021-07-01: User-centered metrics , invited by HyVee Analytics Team , [slides]
2021-04-24: Introduction to Deep Learning (in R and Python) , ASA Traveling Courses
2020-05-27: Machine Learning, Deep Learning and Big Data , ASA Traveling Courses
2020-04-16: How to find a career path in data science? , Magnimind Academy Online Meetup
2019-07-27: Big Data, Data Science and Deep Learning for Statistician , JSM 2019
2018-10-03: Bridging Statistics and Data Science, Fall Technical Conference
2018-06-14: Preparing Statistician to be Successful Big Data Scientist, 2018 ICSA Applied Statistics Symposium
2018-03-23: Marketing Data Science , The University of Iowa
2017-07-30: Preparing Statistician/Statistics Graduates to Be Data Scientist , JSM 2017
The following online tutorials are sponsored by
American Statistical Association(ASA) Statistics in Marketing Section
2018-09-06: Bayesian Nonparametric Customer Base Analysis,
[YouTube],
[Paper]
2018-08-16: Extracting Brand Image Portrayed on Social Media,
[YouTube],
[Paper]
2018-07-19: Optimal Product Design by Sequential Experiments,
[YouTube],
[Paper]
2018-04-26: Randomization for Units in Networked Experiments,
[YouTube]
2018-04-12: A Bayesian Approach to Optimal Pricing Using Business Rules,
[YouTube]
2017-12-14: A Flexible Method for Protecting Marketing Data,
[YouTube],
[Paper]
2017-10-24: Customer Analytics in a Multichannel World,
[YouTube],
[Slides]
2017-08-29: Customer Preference for (Un)biased News,
[YouTube],
[Paper]
2017-07-24: Customer-Based Corporate Valuation,
[YouTube],
[Slides]
2017-06-26: New packages in R Markdown ecosystem,
[YouTube],
[Slides]
2017-04-24: Big Data Cloud Platform in Industry,
[YouTube],
[Slides]
2017-03-28: Unlock Unstructured Social Media Data in Marketing,
[YouTube],
[Slides]
2017-02-28: Putting Big Data & Analytics to Work!,
[YouTube],
[Slides]
2016-08-10: An Introduction to Causal Mediation Analysis,
[YouTube],
[Slides]
2016-07-21: 用R进行市场调查和消费者感知分析,
[YouTube],
[Slides],
[Rcode]
2016-07-14: R for Marketing Research and Analytics,
[YouTube],
[Slides]
2016-06-08: 数据整合和辅助建模技术（1）,
[YouTube],
[Slides],
[Rcode1],
[Rcode2]
2016-06-02: 数据分析一般流程和数据预处理,
[YouTube],
[Slides],
[Rcode]
2016-05-26: Shiny Tutorial,
[YouTube],
[Slides]
2016-04-28: R package regtools and mystery of p-value,
[YouTube],
[Slides]
2016-03-23: A Brief Intro to Deep Learning,
[YouTube],
[Slides]
2016-03-23: Deep Learning in R with MXNet, [YouTube],
[Slides]
2016-01-21: Applied Predictive Modeling,
[YouTube]
2015-11-02: Data Pre-processing Using R & Introduction to R packages:
corrgram,
lucid
2015-07-14: The Ecosystem of R Markdown
About Sponsors
The mission of ASA Statistics in Marketing Section
is to foster the development and application of innovative statistic methodologies
for the resolution of substantive decisions problems in marketing. The scope includes theoretical, methodological,
empirical and applied research oriented toward the practice of marketing. The section encourages the cooperation
between academics and marketing managers to advance statistical science in marketing and stimulate research.
Join ASA Statistics in Marketing here!
This work is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.