which variable among reason for travel, and perceived quality of color, furniture, design, lighting, and layout has the strongest effect on customer satisfaction

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Part 1 - Multiple regression analysis - 50 points x Variables used in the analysis: o SAT - Satisfaction - Average of Sat 1-7 o Travel_reason - What is the most common reason for your travel? o COLOR - Perceived quality of color - Average of COLOR 1, 2, and 3 o FURN - Perceived quality of furniture - Average of FURN 1, 2, and 3 o AEST - Perceived design quality - Average of AEST 1-7 o LIGHT - Perceived quality of lighting - Average of LIGHT 1, 2, 3 and 4 o LAYOUT - Perceived quality of layout - Average of LAYOUT 1, 2, 3, 4 and 5 x Step 1: Recognize research question and formulate hypotheses o Research Question 1 – Do most common reason for travel, and perceived quality of color, furniture, design, lighting, and layout predicts/explains customer satisfaction? o Research

Question 2 for Multiple - Which variable among reason for travel, and perceived quality of color, furniture, design, lighting, and layout has the strongest effect on customer satisfaction? o Formulate Hypothesis x Step 2: Determine how many variables you are comparing o Choose the Significance Level – common ɲ = 0.05 o Recognize independent and dependent variables o Report variable(s) and their types o Model Specification x Step 3: Data requirements and initial analysis o Dependent variable needs to be interval or ratio scaled (continuous) o Independent variables need to be interval or ratio scaled (continuous) or converted to dummy variables ƒ Convert categorical variables to dummy variables o Run analysis o Report sample size o Do dependent and independent variables show variation o Report (Multi)collinearity x

Step 4: Check Assumptions o Report assumptions x

Step 5: If the assumption are met proceed with model estimation x

Step 6: Interpretation and validation o Overall model fit o The effects of the independent variables separately (unstandardized coefficients) o The effects of the independent variables separately (standardized coefficients) o Validation - Split Sample - Randomly select 30 % of cases ƒ Compare the model results 

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