60/3 ÷ 9/5
60/3 × 5/9
300/27
= 100/9
=
60/3 × 5/9
300/27
= 100/9
=
If 8 + 4 = 12, then 12 = _ + _
2 answers:
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Answer:
u as the subject of the given formula is,
Step-by-step explanation:
Given;
v² = u²+2as
To make u the subject of the formula, the following steps are taken;
v² = u²+2as
v² - 2as = u²
take the square - root of both sides of the equation;
Thus, u as the subject of the given formula is,
The next term is double the previous term, so that the -th term is given recursively by
This rule tells us that
and so on, with the explicit rule
for .
If 512 is the -th term in the sequence, then
Answer:
464 students will score between 48 and 75. Using the z-distribution, we measure how many standard deviations each score is from the mean, then find the p-value associated with each score to find the proportion, and from the proportion, we find how many out of 1000.
Step-by-step explanation:
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation
, the z-score of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.
It assumes the scores are normally distributed with a mean score of 75 and a standard deviation of 15.
This means that
How many students will score between 48 and 75?
First we find the proportion, which is the pvalue of Z when X = 75 subtracted by the pvalue of Z when X = 48. So
X = 75
has a p-value of 0.5
X = 48
has a p-value of 0.0359
1 - 0.0359 = 0.4641
Out of 1000:
0.4641*1000 = 464
464 students will score between 48 and 75. Using the z-distribution, we measure how many standard deviations each score is from the mean, then find the p-value associated with each score to find the proportion, and from the proportion, we find how many out of 1000.