Answer:
1) Fail to reject the Null hypothesis
2) We do not have sufficient evidence to support the claim that the mean distance students traveled to school from their current residence was different for males and females.
Step-by-step explanation:
A university administrator wants to test if there is a difference between the distance men and women travel to class from their current residence. So, the hypothesis would be:
The results of his tests are:
t-value = -1.05
p-value = 0.305
Degrees of freedom = df = 21
Based on this data we need to draw a conclusion about test. The significance level is not given, but the normally used levels of significance are 0.001, 0.005, 0.01 and 0.05
The rule of the thumb is:
No matter which significance level is used from the above mentioned significance levels, p-value will always be larger than it. Therefore, we fail to reject the null hypothesis.
Conclusion:
We do not have sufficient evidence to support the claim that the mean distance students traveled to school from their current residence was different for males and females.
The Minitab output from the t-test signifies that there is no statistically significant difference in the distances traveled by men and women at UF to get to class. The t-value and p-value obtained don't give enough evidence to reject the null hypothesis. The degrees of freedom (DF) indicate the number of independent observations in the sample.
The output from Minitab that you've shared is the result of a paired t-test comparing the mean distances traveled by men and women to get to class at UF. The null hypothesis in this context is that there is no difference in the average distances traveled by men and women (Difference = mu (F) - mu (M)). The t-value of -1.05 and the p-value of 0.305 do not provide enough evidence to reject the null hypothesis at the conventional 0.05 level of significance. Therefore, we could interpret the output as not detecting a statistically significant difference between the mean distances men and women travel to get to class at UF.
The 'DF' or degrees of freedom, indicates the number of independent observations in your sample that are free to vary once certain constraints (like the sample mean) are calculated. In this case, DF = 21, which is the sample size (pairs of men and women) minus 1.
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Answer:
Step-by-step explanation:
2x+30=180
2x = 150
x = 75
y=30
Answer:
$85
Step-by-step explanation:
Answer:
the new amount would be $85
Step-by-step explanation:
you do $65 and add 20 because it increased 20
can you please mark me brainlest I would mean a lot
Answer:
Step-by-step explanation:
So, out of a 100% students that drop out, 9,2% is in the range of 16-17 years of age. The conclusion would be, would express the probability of randomly picking a dropout that belong in this set of 16-17 year olds.
Notice that I put "1000" because I want a 0,0092 as a multiplier, because in probability, that represents "9,2%". You actually awnt to always put 100, because that's 100%, but this is just a trick, writing 9,2/100 still works.
Now, for the second bit of information you want to also include that "6,2% white students", which is a subset of the set of 16-17 year olds. and that's a probability, in of itself. Thus, you multiply these two probabilities.
What you want to plug, in your calculator, the follwing expression:
This will give you a number, which you'll have to multiply by 100, to obtain the answer for your problem!
The probability that a randomly selected dropout aged 16 to 17 is white, given the provided statistics, is 67.39%.
The student is asking a question related to conditional probability in the field of Mathematics. The question prompts us to find out the probability that a randomly selected high school dropout in the age range of 16 to 17 is white. To find the answer, we use the following formula:
P(A|B) = P(A ∩ B) / P(B)
Where:
P(A|B) is the probability of event A happening given that event B has occurred.
P(A ∩ B) is the probability of both event A and event B happening together.
P(B) is the probability of event B happening.
From the problem statement, we know that P(B), the percentage of dropouts who are 16-17 years old, is 9.2%. Also, P(A ∩ B), the percent of dropouts who are both white and 16-17 years old, is given as 6.2%. We are supposed to find P(A|B), the probability that a dropout is white given that they are 16-17 years old.
Therefore, by substituting these values into the formula, we get:
P(A|B) = 6.2% / 9.2% = 67.39%
Rounded to two decimal places, the answer is 67.39%. So, there is approximately a 67.39% chance that a random high school dropout aged 16-17 is white.
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Answer:
3x/4 = 5
Step-by-step explanation: