Chemometrics and statistical analysis in raman spectroscopy based biological investigations As mentioned in the chapter 1 chemometrics has become an essential tool in Raman spectroscopy based biological investigations and significantly enhanced the sensitivity of Raman spectroscopy based detection. However there are some open issues on applying chemometrics in Raman spectroscopy based biological investigations. An automatic proce dure is needed to optimize the parameters of the mathematical baseline correction. Spectral reconstruction algorithm is required to recover a fluorescence free Raman spectrum from the two Raman spectra measured with different excitation wavelengths for the shifted excitation Raman difference spectroscopy (SERDS) technique. Guidelines are necessary for reliable model optimization and rigorous model evaluation to ensure high accuracy and robustness in Raman spectroscopy based biological detection. Computational methods are required to enable a trained model to successfully predict new data that is significantly different from the training data due to inter replicate variations. These tasks were tackled in this thesis. The related investigations were related to three main topics: baseline correction statistical modeling and model transfer.