los-angeles-conference-for-statistics

Statistics for the Non-Statistician is a one day conference designed to provide all attendees with the statisical tools needed to apply useful analytical methods to any product or market research. form has been pre-approved by RAPS as eligible for up to 12 credits towards a participant’s RAC recertification upon full completion.

2 day Conference Overview

If statistical analysis is not properly performed and/or understood, a firm can run the risk of distributing the kind of product to the market that ultimately fails, resulting in lost time and money. Statistics of course, requires constant practice. This seminar will be highly interactive and participative. Participants apply their learning of statistics to real-world example data sets. The program begins by providing a basic overview of the most common statistical tools and terms. By the end of day two, course participants will have acquired the skills necessary to read and understand statistical reports contained in the CMC section including statistically sound sampling plan. One of the outstanding features of this learning session is that throughout its duration, it will allow complete interaction of the participants with both an expert instructor and their peers.

Why should you attend

The course is developed for non-statistician whose roles and responsibilities either require interfacing with statisticians or need to perform basic statistical tasks. Most statistical training focus on the formulas and theory instead of the practical implications of the practice of statistics. This course provides practical industry examples putting context to more complex statistical techniques. Most participants have no previous statistical experience, though have interest in learning about how to apply statistical concepts in their job.

Areas Covered in the Seminar:

  • Introduction/Fundamentals – Statistics
  • Summary Statistics
  • Graphical Techniques
  • Hypothesis Testing and Confidence
  • T-test
  • Confidence Intervals
  • Tolerance Intervals
  • Regression
  • Linear Models
  • Lack of Fit
  • Confidence Intervals for Regression
  • Design of Experiments
  • Screening Experiments
  • Fractional Factorial
  • Optimization

There are many elements that will help to indicate the validity of the analytical method that you choose. We will discuss Linearity, Precision, Accuracy, LOD/LOQ, Trending Analysis, Control Charts, Capability Analysis, Sample Size for Mean and Individuals, Sample Size for Attribute and Stability Analysis.

Who will benefit from this one day Conference: Development scientists, statistical researchers, PhD graduates, QA personnel and QC personnel.

AGENDA

Day 1

Lecture 1: Introduction and Basic Overview of Common Statistical Tools
Lecture 2: Hypothesis Testing and Confidence Levels
Lecture 3: Regression Analysis
Lecture 4: Design of Experiments

Day 2

Lecture 1: Method Validation Statistics
Lecture 2: Trending Analysis and Capability
Lecture 3: Sample Size and Risk
Lecture 4: Stability Analysis

SPEAKER: STEVEN WALFISH

President, Statistical Outsourcing Services
Mr. Steven Walfish brings is the founder and President of Statistical Outsourcing Services. He brings nearly 20 years of industrial experience providing statistical solutions to complex business problems. Mr. Walfish was Senior Manager Biostatistics, Nonclinical at Human Genome Sciences in Rockville MD. Mr. Walfish has held positions with PricewaterhouseCoopers, Chiron Diagnostics and Johnson & Johnson. Mr. Walfish holds a Bachelors of Arts in Statistics from the University of Buffalo, Masters of Science in Statistics from Rutgers University and an Executive MBA from Boston University.

LOCATION

Los Angeles, CA Date: October 26th & 27th, 2017 and Time: 9:00 AM to 6:00 PM
Venue : Four Points by Sheraton Los Angeles International Airport
9750 Airport Boulevard, Los Angeles, CA, 90045, United States

$0.00 – $1,295.00
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  • Introduction and Basic Overview of Common Statistical Tools
  • Hypothesis Testing and Confidence Levels
  • Design of Experiments
  • Sample Size and Risk