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Simple Linear Regression Analysis

*The focus of this chapter is the development of some procedures employed in simple linear regression analysis.*

# Topics Covered:

- 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

# Learning Outcomes:

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 ...