T-scores and Z-scores are statistical measures used to determine how far away a data point is from the mean in terms of standard deviations, with Z-scores applied when the population parameters are known and T-scores used when the sample size is small or the population standard deviation is unknown. Both scores are essential in hypothesis testing and confidence interval estimation, providing a standardized way to compare different data sets or distributions.