A consistent correlation between reaction time (RT) and psychometric intelligence (IQ) has resulted in an information processing theory of intelligence; however the weak magnitude of these correlations is problematic. A possible reason for why 'faster is not always smarter' could lie in inhibitory processes of cognitive functioning. This thesis reviews the literature on inhibitory control along with the complex and contentious conceptual issues surrounding it. Furthermore, the weakness of the RT/IQ correlation could be due to the method of analysis and choice of performance variable(s) in chronometric tasks. Historically, reliance on mean RT and parametric analysis of an inherently skewed variable has been the norm. This thesis considers the disadvantages of relying on such 'traditional' performance parameters whilst contrasting their use with more modern methods - specifically the Exponential-Gaussian distributional analysis in the case of RT data and an 'EZ' Diffusion model of decision making. Focusing on response inhibition, a series of three studies is presented, investigating the relationship between this concept and IQ. Study one investigated ocular response inhibition using pro/anti-saccade eye-tracking. Study two investigated the ubiquitous Stroop Colour Word Task (SCWT) along with a directional version of the task. The final study analysed the SCWT in detail; investigating whether the saliency of the distracter element of stimuli could be resulting in a floor effect in performance measures. Across studies, response inhibition was found to be only weakly related to IQ, regardless of analysis method used. For ocular measures, only performance accuracy was related to IQ, in contrast to the Stroop tasks of studies two and three where RT performance was more related to IQ. No correlations with 10 exceeded the magnitude already established between simple and choice RT and IQ with one exception - a moderate correlation (r=.58) between the 'response caution' parameter of the EZ Diffusion model and visual IQ. Exponential-Gaussian and EZ Diffusion models were found to be informative regarding possible processes underlying the Stroop effect and demonstrated their potential to advance understanding of the effect. The conclusion of this thesis was that measures of response inhibition are only weakly related to IQ, with a magnitude similar to other tasks where RT was the dependent variable.