If the p-value is smaller than the level of significance, then it indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null hypothesis is correct.
In this question,
A p-value is a probability, calculated after running a statistical test on data and it lies between 0 and 1. The p-value only tells you how likely the data you have observed is occurred under the null hypothesis.
One of the most commonly used p-value is 0.05. If the value is greater than 0.05, the null hypothesis is considered to be true. If the calculated p-value turns out to be less than 0.05, the null hypothesis is considered to be false, or nullified (hence the name null hypothesis).
A small p-value (< 0.05 in general) means that the observed results are unusual, assuming that they were due to chance only. Now, the smaller the p-value, the stronger the evidence that should reject the null hypothesis.
Hence we can conclude that if the p-value is smaller than the level of significance, then it indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null hypothesis is correct.
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First isolate the group with h in it
minus 2pir^2 from both sides
s-2pir^2=2pirh
divide both sides by 2pir
(s-2pir^2)/(2pir)=h
<span>42.7−<span>(<span>−12.4</span>)
</span></span><span>=<span>42.7−<span>(<span>−12.4</span>)
</span></span></span><span>=<span>42.7+12.4
</span></span><span>=<span>55.1</span></span>
