The interval where the function is nonlinear and decreasing is 0 < x < 4
<h3>How to determine the interval where the function is nonlinear and decreasing?</h3>
The straight lines on the graph are the intervals where the graph is linear
This means that the straight lines on the graph will not be considered
Considering the curve, the graph decrease from x = 0 to x = 4
This can be rewritten as:
0 < x < 4
Hence, the interval where the function is nonlinear and decreasing is 0 < x < 4
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Answer:
20
Step-by-step explanation:
16=1 2/10R + -8
16+8= 12/10R
24=12/10R
R=20
The answer is C.
Since here taxable income is over $77,100 and below $160,850, her tax is $15,698.75 + [.28*($95,000 - $77,100)].
Tax = $15,698.75 + [.28*($17,900)]<span>.
= </span>$15,698.75 + [$5012]<span>.
=</span><span> $</span><span>20,710.75
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Answer:
(1, -3/2)
Step-by-step explanation:
The x coordinate is the same for both endpoints so the x coordinate for the midpoint is 1
The y coordinate for the midpoint is found by adding the two y coordinates and dividing by 2
(2+-5)/2 = -3/2
The midpoint is
(1, -3/2)
Answer:
A.The mean would increase.
Step-by-step explanation:
Outliers are numerical values in a data set that are very different from the other values. These values are either too large or too small compared to the others.
Presence of outliers effect the measures of central tendency.
The measures of central tendency are mean, median and mode.
The mean of a data set is a a single numerical value that describes the data set. The median is a numerical values that is the mid-value of the data set. The mode of a data set is the value with the highest frequency.
Effect of outliers on mean, median and mode:
- Mean: If the outlier is a very large value then the mean of the data increases and if it is a small value then the mean decreases.
- Median: The presence of outliers in a data set has a very mild effect on the median of the data.
- Mode: The presence of outliers does not have any effect on the mode.
The mean of the test scores without the outlier is:

*Here <em>n</em> is the number of observations.
So, with the outlier the mean is 86 and without the outlier the mean is 86.9333.
The mean increased.
Since the median cannot be computed without the actual data, no conclusion can be drawn about the median.
Conclusion:
After removing the outlier value of 72 the mean of the test scores increased from 86 to 86.9333.
Thus, the the truer statement will be that when the outlier is removed the mean of the data set increases.