# A web interface for regression analysis: Walkthrough

**Antoine's data science views**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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After the quick overview, here is a quick walkthrough to some categorical analysis.

**Open the app: **Here

**1. Import the data:**

Here are some homemade data, done with the following R code:

`set.seed(3467)`

x=1:400+rnorm(400,0,1)

y1=x*2.5+40+rnorm(400,0,50)

y2=x*4.5+80+rnorm(400,0,50)

group=rep(c('G1','G2'),each=400)

x=c(x,x)

y=c(y1,y2)

DF=data.frame(x=x,y=y,group=group)

write.csv(DF,'DF.csv')

Click on import data, select your data and set rownames to first column. You should then get a quick overview of the data:

**2. Let’s take a closer looks to our data:***Go to Data->View Data:* and choose x, y and group as the variable to display. We can see that we have two groups (Group1, Group2). Lets take a closer look to x and y distribution

**3. Rename our variables:**

*Go to Data->Data engineering*, and select y as the variable to modify, select rename as the operation to apply and Response as the name. Create the new var !

*Go to Data->View Data:*

**4.Run a first model**

**5.Model Summary**

**6.Interaction model**

**7.Outliers and assumption**

Let’s go to diagnostic->normality. As expected our residuals ar normally distributed.

**8.Save and compare model**

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**Antoine's data science views**.

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