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A small outlier could affect the whole data set because it could reduce the mean, or make the average of the whole data set smaller.
An example would be the data set could be 1, 8, 9, 10
To find the mean you would add everything together then divide it by the number of numbers you just added together. The mean of this set would be 28/4 which equals 7. Now, if the outlier were -8 instead of 1, then the mean would be much different.
~Hope this helped!~
Answer:
a) the probability of A students study for more than 10 hours per week
P(X>10) = 0.117
b) The probability that an student spends between 7 and 9 hour
P(7<x< 9) = 0.9522
Step-by-step explanation:
Step(I):-
Let 'X' be random variable of the normal distributed with a mean of 7.5 hours and standard deviation of 2.1 hours
mean of the Population is = 7.5 hours
standard deviation of the Population = 2.1 hours
Z = 1.1904
The probability of A students study for more than 10 hours per week
P(X>10) = 0.5-A(Z₁) = 0.5 -A(1.1904) = 0.5 - 0.3830 = 0.117
Step(ii):-
Put x=7
put x=9
The probability that an A student spends between 7 and 9 hour
P(7 < x< 9) = A(9) - A(7)
= 0.7142 +0.238
= 0.9522
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<span>y = -x3 + 5x2 - 11x + 55 ||x = 5 one root -125 + 125 - 55 + 55 = 0
using Synthetic Divsion
5 -1 5 -11 55
-5 0 -55
</span><span>-1 0 -11 0
results in:
-x^2 - 11 = 0
x^2 + 11 = 0
x^2 = -11
x = ± i√11
roots are: i√11,-i√11,5</span>