Introduction:
In statistics, it is common to take a sample from a larger population in order to make inferences about the entire population. The sample statistic is a measure calculated from the sample data, while the population parameter is a measure calculated from the entire population. In this question, we are asked to determine the relationship between the sample statistic and the population parameter.

Explanation:
Let's analyze each option to determine its validity:

a) Can never be larger than the population parameter:
This statement is not correct. In some cases, the sample statistic can be larger than the population parameter. This occurs due to random sampling variability. When we take a sample from a population, there is always a chance that the sample does not perfectly represent the entire population. Therefore, the sample statistic may differ from the population parameter. This difference can be positive or negative, depending on the specific sample.

b) Can never be equal to the population parameter:
This statement is also not correct. While the sample statistic is not always equal to the population parameter, it is possible for them to be equal. This occurs when the sample perfectly represents the population, which is a rare scenario. However, it is not accurate to say that the sample statistic can never be equal to the population parameter.

c) Can never be zero:
This statement is not correct either. The sample statistic can be zero if the sample data perfectly reflects the population. For example, if we calculate the mean of a sample and it happens to be the same as the population mean, the sample statistic will be zero. Again, this is a rare occurrence, but it is possible.

d) None of the above:
This option is the correct answer. The sample statistic can be larger than, equal to, or smaller than the population parameter. The relationship between the sample statistic and the population parameter depends on the specific sample and the sampling process. Statistical theory provides methods to estimate the population parameter from the sample statistic and determine the level of confidence in the estimation.

Conclusion:
In summary, the sample statistic can take on any value, including being larger than, equal to, or smaller than the population parameter. The relationship between the two depends on the specific sample and the sampling process. It is important to understand this distinction when making inferences about a population based on sample data.