Multiple regression - P-value=0.000<0.05 reject...

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Introduction
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Multiple regression Determine relationships between other variables Strength of relationships
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1. R2 = 36.4%  36.4% of DV: intention to get into store can be explained by IV: number of meal + Feelings P-value = 0.000 <0.05, reject H 0 IVs ü explanatory power H0: R2 = 0 H1: R2 ≠0
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Feeling (happy/unhappy): p-value= 0.169>0.05 Feeling (bored/ excited): p-value= 0.947>0.05 Number of meal purchased: p-value= 0.000<0.05 H0: ü β1 = 0 H1: β1 ≠ 0 ü β2 = 0 β2≠ 0 β3 = 0 ü β3 ≠ 0 Re- run the model without feeling (happy/unhappy), Feeling (bored/ excited).
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The final regression R2 = 33.9%  33.9% of DV: intention to get int o store can be explained by IV: number of meal P-value = 0.000 <0.05 reject H0 IV ü explanatory power H0: R2 = 0 H1: R2 ≠0
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Unformatted text preview: P-value=0.000&lt;0.05 reject H0 H0: 1 = 0 H1: 1 0 t he intention to get into store= 1.959+ 1.351* number of meal 2. P-value= 0.887&gt; 0.05 accept H0 NO exploratory power of IV. R2 = 0.4% 0.4% of DV: number of meal purchased can be explained by IVs: feeling s towards McDonald H0: R2 = 0 H1: R2 0 Feelings towards McDonald(Bored/excited): P-value= 0.686&gt;0.05 Feelings towards McDonald(happy/unhappy): P-value= 0.686&gt;0.05 accept H0 No relationship between H0: 1 = 0 H1: 1 0 2 = 0 2 0 Limitations Age Group Choice Low external validity-small sample size (n=60) Hard to Imagine-McDonalds in Africa Selection bias-hard to randomly select interviewees...
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This note was uploaded on 03/07/2012 for the course MARKETING eng100 taught by Professor Hass during the Spring '12 term at Central Washington University.

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Multiple regression - P-value=0.000&amp;amp;lt;0.05 reject...

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