Graph the quadrilateral WXYZ with vertices W(–4, –1), X(–6, 1), Y(–8, –1), and Z(–6, –3). Rotate the figure 90° counterclockwise
and graph the rotation.
1 answer:
<h2>Answer:</h2>
Option C
<h2>Step-by-step explanation:</h2>When you rotate a point you could rotate it in Clockwise direction because that's how the hand of a clock move, or rotate it in Counterclockwise direction that's the opposite rotation. In math, counterclockwise is defined as being a positive rotation while clockwise is defined as being a negative rotation. Rotating a whole shape means we're rotating every point in the shape.
On the coordinate plane, consider the point (x,y). To rotate this point by 90° around the origin in counterclockwise direction, you can always swap the x- and y-coordinates and then multiply the new x-coordinate by -1. In a mathematical language this is as follows:
By applying this rule to every point we have:
The figure below shows the original shape in green while the rotated shape is the one in red. As you can see, this figure matches the option C.
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Answer:
0.039 = 3.9% probability that the random sample of 16 people in the elevator will exceed the weight limit
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean and standard deviation
, the zscore 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 pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
If n variables are added, the mean is and the standard deviation is
In this problem:
What is the probability that the random sample of 16 people in the elevator will exceed the weight limit?
This is 1 subtracted by the pvalue of Z when X = 2750. So
By the Central Limit Theorem
has a pvalue of 0.961
1 - 0.961 = 0.039
0.039 = 3.9% probability that the random sample of 16 people in the elevator will exceed the weight limit
The time it would take for the bacteria to reach 1119 is 5.83 hours
<h3>Calculations and Parameters:</h3>Given the function:
- Initial amount= 50
- amount after 3 hours= 80
To find the exponential growth;
80 =
If there is a constant growth, then to get to 1119:
1119=
3.8 = 0.533*t
t= 5.83 hours
Therefore, it would take 5.83 hours for the bacteria to increase to 1119.
Read more about exponential growth here:
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