1B: -3(9x-q)
-27x + 3q
Step 1: Distribute the -3 to the 9x to get -27x.
Step 2: Distribute the -3 to the -q.
2B: 2(12+5p)
24 + 10p
Step 1: Distribute the 2 to the 12 to get 24.
Step 2: Distribute the 2 to the 5p to get 10p.
3B: -7(-8y+7)
56y - 49
Step 1: Distribute the -7 to the -8y to get 56y.
Step 2: Distribute the -7 to the 7 to get -49.
4B: 10(2+7c)
20 + 70c
Step 1: Distribute the 10 to the 2 to get 20.
Step 2: Distribute the 10 to the 7c to get 70c.
5B: -8(7+11k)
-56 - 88k
Step 1: Distribute the -8 to the 7 to get -56.
Step 2: Distribute the -8 to the 11k to get -88k.
6B: -(3-7u)
-1(3-7u)
-3 + 7u
Step 1: Place a 1 after the negative symbol to symbolize -1.
Step 2: Distribute the -1 to the three to get -3.
Step 3: Distribute the -1 to the -7u to get 7u.
7B: -6(5p + s)
-30p - 6s
Step 1: Distribute the -6 to the 5p to get -30p.
Step 2: Distribute the -6 to the s to get -6s.
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Answer:
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Step-by-step explanation:
done ur test
Answer:
The sequence is: Refection across y-axis, Horizontal Shrink, Horizontal Translation and Reflection across x-axis.
Step-by-step explanation:
Since, we are given f(x) = square root x.
The sequence of transformations which transform f(x) into g(x) is given by:
1. Reflection across y-axis i.e. f( x ) to f( -x )
2. Horizontal Shrinking i.e. f( -x ) to f( -x/2 )
3. Horizontal Translation i.e. f( -x/2 ) to f( -x/2 + 3 )
4. Reflection across x-axis i.e. f( -x/2 + 3 ) to -f( -x/2 + 3).
The step by step graphical representation can also be viewed below.
Answer:
z = 36 rolls , probability for getting 7 = 1/6
Step-by-step explanation:
A die has 6 possible outcomes, which sums to 36 for two dice for every value on both dice.
The outcomes for rolling both dice for 36 times gives 6 possible outcomes summing to 7, that is, (1, 6), (2, 5), (3, 4), (4, 3), (5, 2), and (6, 1).
There the probability of getting a sum dice of 7 is:
= 6 / 36 = 1/6
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.