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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The term parameter space as used in data-fitting (see for example "Data Reduction and Error Analysis for the Physical Sciences" by Bevington and Robinson), refers to the hypothetical space where a "location" is defined by the values of all optimizable parameters. For example, if we fit data using a function which has 10 optimizable parameters, each of these parameters is seen as a dimension and the parameter space in this case is 10-dimensional. Every "location" then corresponds to a ² (chi-squared) value indicating the goodness-of-fit, hence we have a "field" in our 10-dimensional space. Following this "field" downwards leads us to the "location" in parameter space with the lowest ², i.e. the optimum parameter values.