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:
Option C.
Step-by-step explanation:
Hey there!
The points are; (-4,-4) and (-4,-10).
<u>Use </u><u>distance</u><u> formula</u><u>.</u>
~ Put all values.
~ Simplify it.
Therefore, distance between the points is 6 units.
<em><u>Hope</u></em><em><u> it</u></em><em><u> helps</u></em><em><u>.</u></em><em><u>.</u></em><em><u>.</u></em>
The answer is 30 because you have to multiply the two together
Step-by-step explanation:
A rigid transnformation is also know as isometrie. <u>This are transformations of the plane that preserves the lengths</u>. There are 3 types of isometries and each one can be combined with the others.
- Reflection (First figure)
- Translation (second figure)
- Rotation (third figure)
Combining this transformations you will be able to transform ΔJKL onto ΔPQR
