Simple Linear Regression Analysis
The focus of this chapter is the development of some procedures employed in simple linear regression analysis.
- Basic concepts of regression analysis
- Fitting a straight line by least squares
- Unbiased estimation of error variance
- Tests and confidence intervals for the regression coefficients of the simple linear regression model
- Determination of confidence intervals for
- Determination of a prediction interval for a future observation Y
- Inference about the correlation coefficient
- Residual analysis
After studying this chapter, the reader will be able to
- Fit a simple linear regression model to a given set of data, and perform a residual analysis to check the validity of the model under consideration.
- Estimate the regression coefficients using the method of least squares, and carry out hypothesis testing to test whether the first-order regression model is an appropriate fit to the given data.
- Estimate the expected response, predict future observation values, and find their confidence intervals using the given confidence ...