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:
a. 20
b. 30
c. 75
b. 600 / 2000 * 100% (Change it to same unit)
3 / 10 * 100%
30%
You can slove every question by this method.
and dont forget to give me the brainest.
Answer:
see below
Step-by-step explanation:
First of all, you want to find the data set the matches the extreme values of 5 and 35. That eliminates the 2nd and 4th choices.
Then you want to find the data set that has a median of 15. The first data set has a middle value (median) of 20, so that choice is eliminated.
The data set of the 3rd choice matches the box plot extremes, median, and quartile values.
P (A and B) = P(A) * P(B)...answer is D
