Sawtooth Software Conference 2019 | San Diego, CA, USA | September 23–27

Sawtooth Solutions #20: 2004 Summer

Sawtooth Software Conference 2004 Program Set

We are pleased to announce the program for the 2004 Sawtooth Software Conference, to be held in San Diego, CA, October 6-8, 2004. Our conferences are well-known for their practical focus, friendly environment, accessible presentations, and excellent food. They are not sales events for our software, but forums for discussing a variety of issues related to conjoint/choice analysis, computer/web interviewing, and other quantitative methods. Typically about one-quarter of the attendees are not Sawtooth Software users.

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Workshop for Newcomers to Conjoint Analysis

We often hear from people very new to conjoint analysis who want to receive instruction and training. An excellent opportunity is the 1.5-day introductory class on conjoint analysis held just prior to our regular research conference in San Diego, CA, on October 4-5 (Monday and Tuesday). Tom Pilon, Ph.D. will be conducting the sessions. Tom has extensive experience in applying conjoint methods to business problems.

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Update on Relative Conjoint Analysis Usage

In April, 2004 we completed a second wave of our annual customer feedback survey. For those who participated, thank you! Aside from asking users how we might improve, we also collected some information that may be of interest to you. Customers specified what percent of projects over the last 12 months employed which specific conjoint methods.

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SSL (Secure Socket Layer) Available with Sawtooth Software Hosting Services

Many of our SSI Web users have been taking advantage of our web survey hosting services. Even though our software enables users to host their own projects on either Windows or Unix servers, some users find it more convenient to ask us to host surveys for them. Our basic hosting package for a small project starts at $250.

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Testing for Significant Differences in Conjoint Analysis

When analyzing conjoint analysis data, we may wish to conduct statistical tests to detect significant differences. Common situations include...

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