R regress one variable on all the other variables

To regress one variable on all the other variables in R, you can use the lm() function. Here are the steps:

1. Load the dataset into R using the appropriate function, such as read.csv() for a CSV file or read.table() for a tab-delimited file.
2. Use the lm() function to create a linear regression model. The syntax is lm(y ~ x1 + x2 + ..., data = your_data), where y is the dependent variable and x1, x2, etc. are the independent variables.
3. Extract the summary of the regression model using the summary() function. This will provide information about the coefficients, standard errors, t-values, p-values, and R-squared value.
4. Analyze the output to interpret the coefficients, standard errors, t-values, and p-values to understand the relationships between the variables.

These steps will allow you to regress one variable on all the other variables in R and interpret the results.