< Research statistics > Reference : https://docs.google.com/spreadsheets/d/1Suz_vLMGHg4h8H81zbHrCPO5VcDP36N5/edit?usp=sharing&ouid=110640191752541793060&rtpof=true&sd=true https://docs.google.com/document/d/1R65IcAOFeRvmdhZ1zgR6xm6h7exrXi3l/edit?usp=sharing&ouid=110640191752541793060&rtpof=true&sd=true https://drive.google.com/drive/folders/1uyG49PKHl1rGcQ_-Je9bDKbKc9c659Mr?usp=sharing Could you please show the steps as well? I can't seem to get it right

< Research statistics >

Reference :

https://docs.google.com/spreadsheets/d/1Suz_vLMGHg4h8H81zbHrCPO5VcDP36N5/edit?usp=sharing&ouid=110640191752541793060&rtpof=true&sd=true

https://docs.google.com/document/d/1R65IcAOFeRvmdhZ1zgR6xm6h7exrXi3l/edit?usp=sharing&ouid=110640191752541793060&rtpof=true&sd=true

https://drive.google.com/drive/folders/1uyG49PKHl1rGcQ_-Je9bDKbKc9c659Mr?usp=sharing

<3 questions>

Could you please show the steps as well? I can't seem to get it right

1. Code all five attributes (including price) using dummy variables. Outline the coding plan.Type in the ranks and the dummy variables for each of the 18 profiles into a spreadsheet. Convert the rank order so that the higher the number the more preferred the object. In the table above, the most preferred object is ranked 1 (Hint: Subtract each rank given in the last column from 19 to get the converted ranks.)

2.Compute the correlation matrix of the dummy variables. What do you notice in the correlation matrix? What does this say about the particular set of 18 profiles that were presented to the respondent?

3. Run a regression using the rank as the dependent variable and the dummy variables as the predictors. (Disregard your suspicion that the dependent variable is ordinal scaled and I said in class that the dependent variable for regressions must be interval scaled!) The regression coefficients of the dummy variables can be treated as utilities.