<span>D.It has affected the fates of a space probe and a commercial airline flight.</span>
A. Polysaccharide, this is because polysaccharides have cellulose which make the grass stand up.
A blood clot forms in a fibrous network of protein is called A) Fibrinogen.
Answer:
I am pretty sure that the answer is A.
Explanation:
Protein kinases regulate the cell cycle by giving the "go-ahead" or "stop" signal at checkpoints in the cycle. A mutation/disruption in the protein kinases can result in it not doing its job properly. As a result, it can give the 'go-ahead' signal to all cells (mutated or not) to continue through the cell cycle. A distrupted kinase will infleunce the enviornment for a cancer cell as the cancer cell can continue to divide continuously.
I do not think the answer is D because G-couped receptirs are not involed in the regulation of the cell cycle. Additionally, I do not think the answer is C since the production of cAMP (a secondary messgenger amplifies transduction signals; this doesn't have anything to do with cancer?) Finally, between A and B I know that a direct result of cancer is due to a distruption in either protien kinases or growth factors (not in the answer choices). Since one of the factors that leads to cancer is present in answer choice A, I think that is the one. However, this is just my reasoning, I am not 100% sure!
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
