When data are collected and a sample statistic is computed, it almost always differs from the claimed value of the corresponding population paramter. What are the two reasons that explain why this happens?

Is unbiased estimator

Step-by-step explanation:

In statistics, Numerical characteristics derived from population data is referred to as parameter, while those derived from the sample data are called statistic. When a sample is drawn from a particular population, the statistic of such sample could be used as either a point or interval estimate of the population. However, the estimator derived from the sample in most cases isn't equal to the exact parameter value. When this happens, that is, when population parameter equals the estimate of the sample statistic, then we have an unbiased estimator.

y=1/4x-4

step-by-step explanation:

3/6 chance

step-by-step explanation:

half of the nubers are odd numbers (1,3,5) which in that case if you would be told to simplify it would be 1/2