genetic vs statistic regression a comparison lkin
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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LRM yields one solution, which finds 50% of responses in 4th decile. GenIQ outdoes LRM by findings 75% of responses. GenIQ is flexible as it evolves many solutions. See slides #38 - #40.
Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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Bruce Ratner, Ph.D. www.GenIQModel.com
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