The total length of the fence is 48 m if the rectangular swimming pool measures 7.5 m by 4.5 m.
<h3>What is rectangle?</h3>
It is defined as the two-dimensional geometry in which the angle between the adjacent sides are 90 degree. It is a type of quadrilateral.
It is defined as the area occupied by the rectangle in two-dimensional planner geometry.
The area of a rectangle can be calculated using the following formula:
Rectangle area = length x width
It is given that:
A rectangular swimming pool measures 7.5 m by 4.5 m.
It is completely surrounded by a fence parallel to each edge of the pool and at a distance of 3 m from each edge of the pool.
The total length of the fence = 2(7.5+3×2 + 4.5+3×2)
The total length of the fence = 2(7.5+6 + 4.5+6)
The total length of the fence = 2(24)
The total length of the fence = 48 m
Thus, the total length of the fence is 48 m if the rectangular swimming pool measures 7.5 m by 4.5 m.
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The remainder is or answer is 6
Answer:
ok so if equilateral triangle has 1 inch and box has 9 inch of height, the lateral area would be 27 square-inch
Step-by-step explanation:
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.
