Answer:
Step-by-step explanation:
we have
we know that
Substitute the values in the expression
Please answer correctly :>>>>
1 answer:
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This load will weigh 1.5 TONS ALTOGETHER.
So, the truck is delivering a
ton of cement blocks, and a 
of bricks. To find how much this load weighs, we'd have to add the two fractions together, which proves to be quite easy, because the denominators are already the same, so we wouldn't have to change anything.
+ = 
And now, we would want to convert that fraction into a whole number, or at least a decimal, to find how many tons the truck is carrying. So we would divide. Once the work is done, here is what would happen:
12 ÷ 8 = 1.5
And there's your answer. The truck is carrying 1.5 TONS.
So, the truck is delivering a
And now, we would want to convert that fraction into a whole number, or at least a decimal, to find how many tons the truck is carrying. So we would divide. Once the work is done, here is what would happen:
12 ÷ 8 = 1.5
And there's your answer. The truck is carrying 1.5 TONS.
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.