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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Answer:
no his prediction is not correct. there would be 90 window panes
Step-by-step explanation:
12 panes in 2 windows so 1 window has 6 panes. multiply the 15 windows by 6 panes to get the total of 90 panes
12/2=6
6x15=90
Answer:
16
Step-by-step explanation:
The square numbers are
1² = 1
2² = 4
3² = 9
4² = 16 ← this is the closest perfect square
5² = 25 (not applicable, over 22)
