Hello,
I need so advice on this statistics project that I'm working on
I need to measure brand equity of a company (dependent variable) with multiple independent variables such as loyalty, popularity, familiarity, etc.
A survey was conducted where many people gave a score for each independent variable for that one company. I was thinking of multiple linear regression but I'm not sure if I'm on the right track.
Please let me know what are your inputs
selecting the right tool for analysis is the most step. Along with the understanding of objectives, one must be clear about the type of scale used for data collection. as your analysis is multivariate with 1 dependent and more than 1 independent variable, following tools can be used:
multiple regression (if all IV are metric)
n-way ANOVA (if all IV are non metric)
n-way ANCOVA or Regression with dummy variable (if IV are mixed)
where n is the number of non metric independent variable
Note: Assuming your dependent variable is metric
It depends on how exactly you define those variables, I'd say. Then you have to think about what relationship would be logical, and regression will then produce the parameter values and uncertainties.
I believe, in your case, you may use multiple regression analysis. Multiple regression analysis is a statistical technique that can be used to analyze the relationship between a single dependent variable and several independent variables.
If you set customer satisfaction (brand satisfaction) or brand image as the mediator, you may be considered PLS-SEM. But if only independent variables, suggest using Multiple regression analysis. Agree with the professors, thank you for the good question and answers.
All the best,
- Badges
- Science topic
- Similar topics
- Filing