A) If the data is weight, the \( z \)-score for someone who is overweight would be: negative zero positive B) If the data is IQ test scores, an individual with a negative z-score would have a: low IQ average IQ high IQ watch very little TV watch the average amount of TV watch a lot of TV data is time spent watching TV, an individual with a z-score of zero would: D) If the data is annual salary in the U.S and the population is all legally employed people in the U.S., the z-scores of people who make minimum wage would be: negative zero positive

When discussing z-scores, it’s essential to understand how they relate to a standard normal distribution. A positive z-score means a value is above the mean, while a negative z-score indicates it falls below the average. So, in your example, someone overweight typically has a higher weight than the average, resulting in a positive z-score! In terms of IQ tests, a negative z-score indicates a score lower than the average IQ, which is set at 100. Thus, an individual with such a z-score is more likely to be classified as having a low IQ. As for minimum wage earners, their earnings are generally below the average salary in the U.S., leading to negative z-scores as well!