The Survey of Consumer Expectations is a monthly survey of U.S. households by the New York Federal Reserve Bank. The people are asked about how much the expect to spend, how high they expect inflation to be, their employment situation, and whether they are searching for a job. (Wikipedia).
Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
From playlist Statistics (Full Length Videos)
Statistics Lecture 7.2: Finding Confidence Intervals for the Population Proportion
https://www.patreon.com/ProfessorLeonard Statistics Lecture 7.2: Finding Confidence Intervals for the Population Proportion
From playlist Statistics (Full Length Videos)
Introduction to Engagement Rate | Marketing Analytics for Beginners | Part-12
Engagement rate measures the amount of interaction the content is generating relative to reach, impressions, and views. Engagement rate is one of the core metrics to measure the success of a digital marketing campaign. This video discusses the importance of engagement rate and different
From playlist Marketing Analytics for Beginners
Statistics 5_1 Confidence Intervals
In this lecture explain the meaning of a confidence interval and look at the equation to calculate it.
From playlist Medical Statistics
An introduction to the typical ways that public opinion is measured.
From playlist Exploring Data
Statistics Lecture 5.2: A Study of Probability Distributions, Mean, and Standard Deviation
https://www.patreon.com/ProfessorLeonard Statistics Lecture 5.2: A Study of Probability Distributions, Mean, and Standard Deviation
From playlist Statistics (Full Length Videos)
Webinar: If I build it, will they come? Understanding Product-Market Fit
Learn more at: https://stanford.io/370yNcZ So your company has a product idea. How do you know if this product is worth building? Will there be a demand for it? Enter: product-market fit. Put simply, product-market fit means that there are enough people out there who will buy what your c
From playlist Leadership & Management
Statistics Lecture 3.4: Finding Z-Score, Percentiles and Quartiles, and Comparing Standard Deviation
https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.4: Finding the Z-Score, Percentiles and Quartiles, and Comparing Standard Deviation
From playlist Statistics (Full Length Videos)
TEEB for Business-Biodiversity Impacts and Dependencies: TEEB @ Yale
Why are companies interested in biodiversity? What industries are most responsible for and/or vulnerable to biodiversity loss?
From playlist TEEB @ Yale
We present the results from our embarrassing survey and find out how many of you pick your nose. This was an application of Randomised Response. Then, after a little introduction to statistics, we invite you to take part in another embarrassing survey using a slightly different method: Hav
From playlist My Maths Videos
RailsConf 2018: What's in a price? How to price your products and services by Michael Herold
What's in a price? How to price your products and services by Michael Herold So you have something new to sell: maybe your first book or a hip new SaaS. How do you decide the price? How do you know you're not overpricing? Or underpricing? Why, oh why, did you ever think to sell something?
From playlist RailsConf 2018
Consumer Responses to Electric Vehicles
(April 14, 2010) Tom Turrentine, Director of UC Davis's Plug-in Hybrid Electric Vehicle Research Center, discusses recent anthropological research on changes in consumer behavior in response to the recent rapidly growing and changing alternative-fuel vehicle market and how these responses
From playlist Lecture Collection | Energy Seminar
Causal Behavioral Modeling Framework - Discrete Choice Modeling of Consumer Demand
There are increasing demands for "causal ML models" of the agent behaviors, which enable us to unbox the complex black-box models and make inferences or do proper counterfactual simulations. Many applications (especially in Marketing) intrinsically call for measurement of the causal impact
From playlist Fundamentals of Machine Learning
CERIAS Security: Privacy Policies in Web-based Healthcare 5/5
Clip 5/5 Speaker: Julie Earp · North Carolina State University The Health Insurance Portability and Accountability Act of 1996 (HIPAA) has resulted in the presence of very descriptive privacy policies on healthcare websites. These policies are intended to notify users about the organi
From playlist The CERIAS Security Seminars 2006
Lecture 4: Quality Function Deployment (QFD) and House of Quality
MIT 22.033 Nuclear Systems Design Project, Fall 2011 View the complete course: http://ocw.mit.edu/22-033F11 Instructor: Dr. Michael Short License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 22.033 Nuclear Systems Design Project, Fall 2011
Empathic Media: The Case of Gaming
From the Interactive Media & Games Seminar Series; Andrew McStay, a Reader in Advertising and Digital Media, Bangor University examines how gaming is a leading example of empathic media because it was first within the media industry to market rich consumer-level biometric entertainment; bu
From playlist Interactive Media & Games Seminars WINTER 2016
Linking Data Quality with Customer Value
To learn more about Wolfram Data Summit, please visit: http://www.wolframdatasummit.org/ Established as a forum for leaders of the world's great data repositories, the Wolfram Data Summit has become an annual event for those interested in the latest innovations in data and data science. T
From playlist Wolfram Data Summit 2016
OpenStack User Committee Update & Survey Results
Speakers: Ryan Lane (Wikimedia), JC Martin (eBay), Tim Bell (CERN) Representing the user committee, we will review the current status of the OpenStack user committee, its scope, the plans for next year along with the input from the user groups, industry sectors and foundation members. Rep
From playlist OpenStack Summit Portland 2013
Evaluating Time Series Models : Time Series Talk
How do we evaluate our time series models? How can we tell if one model is better than another?
From playlist Time Series Analysis