Final answer:
The question compares two methods of FIT calculations, likely in the context of statistical fit analysis, such as the goodness-of-fit test and least squares regression. These methods can be compared by how they assess data fit, their computational approach, and their applications in different studies or models.
Step-by-step explanation:
The question asks to compare and contrast two methods of FIT calculations. FIT typically refers to Fit Index Technologies, although it's not clearly defined in the question, it can also relate to statistics, specifically in the context of goodness-of-fit tests or least squares regression analysis. One might compare two methods by looking at how they calculate the fit of data to a model or prediction. For example, one could compare the least squares method to another method, such as the maximum likelihood estimation.
- In the given references, there is mention of a goodness-of-fit test, which can be used to compare observed data with expected data under a given hypothesis. This often involves calculating expected frequencies and using a chi-square test to determine how well the data fits a theoretical distribution.
- On the other hand, the least squares method is used to fit a line to a set of data points by minimizing the sum of the squares of the vertical distances of the points from the line.
Methods can further be compared based on ease of use, the accuracy of fit, assumptions made, and application in various fields of study, for instance, in the estimation of energy expenditure in resistance training activities or comparing the trajectories of a golf shot. Excel can be a useful tool for graphically comparing regression lines and assessing the fit of the lines to the data.