Answer: D) the significance level of the test
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Explanation:
The significance level of the test, also known as "alpha", is the probability of making a type 1 error. A type 1 error is where you reject the null hypothesis but it was true all along.
The null hypothesis is where we test a certain probability distribution (eg: normal distribution). Specifically we gather a sample of values and compute the test statistic. If the probability of getting that test statistic or more extreme is smaller than alpha, then we reject the null. This probability value is known as the p-value.
If you lower the alpha value, then that will make it more likely you do not reject the null. Consider an example where alpha = 0.10 to start with. If you get a p-value of 0.02, then you would reject the null. The same would apply for alpha = 0.05; however, with alpha = 0.01, the p-value is no longer smaller than alpha. At this point we do not reject the null. Your textbook may use the phrasing "fail to reject the null".
Going in the opposite direction, increasing the alpha value will make it more likely to reject the null. Each time you adjust the alpha value, keep the p-value to some fixed number (between 0 and 1).
Answer:
Ge I Joe 02 04 Soccer balls height
Answer:
30 students
Step-by-step explanation:
3 students = 10% of the class.
x students = 90% of the class.
(If more, less divides. Let x be the subject. Since we know 10% of the class already, we have to find the remaining 90% that is 100% - 10% = 90%.)
x = 90%/ 10% × 3 students. ( the percentage signs cancel out and so do the zero's.)
x= 9/1 × 3 students ( 9/1 is the same as 9)
x= 27 students
(To find the total, you must add the 10% of the students to the remaining 90% of the students in the class.)
Total number of students in the class = 27 students + 3 students
= 30 students
Answer:
13
Step-by-step explanation:
Answer: it’s C
Step-by-step explanation:
