What are the coordinates of point Q? HELPP QUICK !!!
1 answer:
Answer:
The coordinates of point Q are
Step-by-step explanation:
The coordinates of point Q can be found looking at the graph
We need to find the value of x-coordinate and y-coordinate by looking at graph.
Check the value of x-coordinate that matches point Q similarly check the value of y-coordinate that matches point Q
Looking at the graph Point Q is at x=4 and y=2.5 or
So, The coordinates of point Q are
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Answer:
option D is rational
Step-by-step explanation:
A rational number is a number that can be written in the form of fraction or integer
here in the given question
A) 1.5 + √1.5
now,
√1.5 is not rational as √1.5 = 1.2247448713915890490986420373529
hence A is not rational
b) 12 - √12
√12 is not rational as √12 = 3.4641016151377545870548926830117
hence B is not rational
c)
here,
is not rational
D)
now,
√25 = 5
hence,
=
= 5
therefore,
option D is rational
Answer: 687
Step-by-step explanation:
normally distributed
μ = 498
σ = 108
Top 4%
P(X > a) = 0.04
P(Z > a-498/108) = 0.04
Using the table attached, for the top 4%:
0.50 - 0.04 = 0.46
a-498/108 = 1.75
a-498 = 189
a = 687
The minimum score for the scholarship is 687.
Answer:
The system of hypothesis for this case are:
Null hypothesis:
Alternative hypothesis:
A type of error I for this case would be reject the null hypothesis that the true mean is equal than 150 when actually is not true.
Step-by-step explanation:
Previous concepts
A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".
The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".
The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".
Type I error, also known as a “false positive” is the error of rejecting a null hypothesis when it is actually true. Can be interpreted as the error of no reject an alternative hypothesis when the results can be attributed not to the reality.
Type II error, also known as a "false negative" is the error of not rejecting a null hypothesis when the alternative hypothesis is the true. Can be interpreted as the error of failing to accept an alternative hypothesis when we don't have enough statistical power.
Solution to the problem
The system of hypothesis for this case are:
Null hypothesis:
Alternative hypothesis:
A type of error I for this case would be reject the null hypothesis that the true mean is equal than 150 when actually is not true.