Which measurement is most accurate to describe the length of a ladybug?
1 answer:
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Answer:
See below:
Step-by-step explanation:
Hello! I hope you are having a nice day!
We can solve this problem in two steps; solving and theory.
I'll go and start off with the theory part!
Theory
We know that in geometry there are many types of triangles that have various different angles. With that, there are a few special triangles that people have made formulas for, one being a 30, 60, and 90 degree triangle.
The theorem states that the hypotenuse is , the side opposite to 60 degrees is
, and the bottom is
.
Solving
We can solve this problem in a step, we just need to know what the theorem said and implement it here, since we know the values of the sides of the triangle, we can solve it by finding out the opposite side and applying the theorem rules.
If we look at the graph, we can see that the part of the side opp. of 60 degrees is 4, that means that
would be double of 4, which is 8.
Therefore your answer would be:
Cheers!
Answer:
a)Null hypothesis:
Alternative hypothesis:
b) A Type of error I is reject the hypothesis that is equal to 40 when is fact
, is different from 40 hours and wish to do a statistical test. We select a random sample of college graduates employed full-time and find that the mean of the sample is 43 hours and that the standard deviation is 4 hours. Based on this information, answer the questions below"
Data given
represent the sample mean
population mean (variable of interest)
s=4 represent the sample standard deviation
n represent the sample size
Part a: System of hypothesis
We need to conduct a hypothesis in order to determine if actual mean is different from 40 , the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
Part b
In th context of this tes, what is a Type I error?
A Type of error I is reject the hypothesis that is equal to 40 when is fact [tex]\mu is equal to 40
Part c
Suppose that we decide not to reject the null hypothesis. What sort of error might we be making.
We can commit a Type II Error, since by definition "A type II error is the non-rejection of a false null hypothesis and is known as "false negative" conclusion"