Regression analysis in thesis

In linear regression, the model specification is that the dependent variable, y i {\displaystyle y_{i}} is a linear combination of the parameters (but need not be linear in the independent variables ). For example, in simple linear regression for modeling n {\displaystyle n} data points there is one independent variable: x i {\displaystyle x_{i}} , and two parameters, β 0 {\displaystyle \beta _{0}} and β 1 {\displaystyle \beta _{1}} :

I need to carry out multiple regression analysis on ordinal (satisfaction measures) independent variables. There are three parameters each categorised into factors and subfactors (variables). Each subfactor includes multiple questions to get satisfaction rating. Thus summing up the scores from questions to subfactors; subfactors to factors; factors to each respective paramater and finally combined score of all three parameters considered as score of the aspect of interest. My first question is whether the method is correct, and second is which specific regression analysis method should I use. Sample size is 300 households within 16 clusters equally divided into two categories.

# Calculate Relative Importance for Each Predictor
library(relaimpo)
(fit,type=c("lmg","last","first","pratt"),
   rela=TRUE)

# Bootstrap Measures of Relative Importance (1000 samples)
boot <- (fit, b = 1000, type = c("lmg",
  "last", "first", "pratt"), rank = TRUE,
  diff = TRUE, rela = TRUE)
(boot) # print result
plot((boot,sort=TRUE)) # plot result

It is possible to do multiple regression in Excel, using the Regression option provided by the Analysis ToolPak . The trouble is that you have to do this one regression at a time through the point-and-click UI - there is no way to do it with formulas - so it's not really practical to test different base-temperature combinations to find the optimal base temperatures. (Note we say plural "base temperatures" because usually the HDD base temperature and the CDD base temperature are different, with the CDD base temperature typically being higher.)

This course takes place online at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement :
About 15 hours per week, at times of  your choosing.

Regression analysis in thesis

regression analysis in thesis

It is possible to do multiple regression in Excel, using the Regression option provided by the Analysis ToolPak . The trouble is that you have to do this one regression at a time through the point-and-click UI - there is no way to do it with formulas - so it's not really practical to test different base-temperature combinations to find the optimal base temperatures. (Note we say plural "base temperatures" because usually the HDD base temperature and the CDD base temperature are different, with the CDD base temperature typically being higher.)

Media:

regression analysis in thesisregression analysis in thesisregression analysis in thesisregression analysis in thesis