Imagine you are surveying a population of a mountain range where the inhabitants live in the valleys with no inhabitants on the large mountains between. If your sample area is the valleys, and you use this to estimate the population across the entire mountain range, <u>you overestimate the actual population size</u>
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Explanation:
- An estimate that turns out to be incorrect will be an overestimate if the estimate exceeded the actual result, and an underestimate if the estimate fell short of the actual result.
- The mean of the sampling distribution of a statistic is sometimes referred to as the expected value of the statistic. Therefore the sample mean is an unbiased estimate of μ.
- Any given sample mean may underestimate or overestimate μ, but there is no systematic tendency for sample means to either under or overestimate μ.
- Bias is the tendency of a statistic to overestimate or underestimate a parameter. Bias can seep into your results for a slew of reasons including sampling or measurement errors, or unrepresentative samples
<span>B)The immunity they receive in the womb from their mother is temporary.
I believe this as the mother passes antibodies to the child through the last three months of pregnancy, and this is a passive immunity </span>
Answer:
The deposits truly depend on climate and the organisms from long ago that make fossil fuels <em>out of fossilized remains</em>. At that rate, the fuel will not be evenly distributed, rather split into some form of groups.
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