Answer:
D.
Step-by-step explanation:
<u>Explanation for part 1.</u>
To find the mean, find total then divide by number of data set
For college salaries
Sum=41+67+53+48+45+60+59+55+52+52+50+59+44+49+52=786
Number of samples=15
Mean= 786/15 =52.4 * $1000=$52400
For High school salaries
Sum=23+33+36+29+25+43+42+38+27+25+33+41+29+33+35=492
Number of samples =15
Mean= 492/15 = 32.8 *$1000= $32800
College grads make more money according to the means.
<u>Explanation for part 2.</u>
Treat the data as part of coordinates and graph then on the same scale and axis to visualize the trend and make comparison.In this case, the graph for the line of best fit is linear as attached.
Answer:
Step-by-step explanation:
Since the length of time taken on the SAT for a group of students is normally distributed, we would apply the formula for normal distribution which is expressed as
z = (x - u)/s
Where
x = length of time
u = mean time
s = standard deviation
From the information given,
u = 2.5 hours
s = 0.25 hours
We want to find the probability that the sample mean is between two hours and three hours.. It is expressed as
P(2 lesser than or equal to x lesser than or equal to 3)
For x = 2,
z = (2 - 2.5)/0.25 = - 2
Looking at the normal distribution table, the probability corresponding to the z score is 0.02275
For x = 3,
z = (3 - 2.5)/0.25 = 2
Looking at the normal distribution table, the probability corresponding to the z score is 0.97725
P(2 lesser than or equal to x lesser than or equal to 3)
= 0.97725 - 0.02275 = 0.9545
4y-8>10
Add 8
4y-8+8>10+8
4y>18
Now divide both sides by 4
4y/4 > 18/4
y>9/2
Now let's see if it will be true
Replace y by its value
4(9/2)-8>10
36/2 -8 > 10
18-8 > 10
10 > 10
That's false because 10 can not smaller than 10
so it should be = instead
Answer : False
I hope that's help:)
Answer:
-45 is xn
The x=3 and x=-15 multiply them together which is the answer to xn
Answer:
Our answer is 0.8172
Step-by-step explanation:
P(doubles on a single roll of pair of dice) =(6/36) =1/6
therefore P(in 3 rolls of pair of dice at least one doubles)=1-P(none of roll shows a double)
=1-(1-1/6)3 =91/216
for 12 players this follows binomial distribution with parameter n=12 and p=91/216
probability that at least 4 of the players will get “doubles” at least once =P(X>=4)
=1-(P(X<=3)
=1-((₁₂ C0)×(91/216)⁰(125/216)¹²+(₁₂ C1)×(91/216)¹(125/216)¹¹+(₁₂ C2)×(91/216)²(125/216)¹⁰+(₁₂ C3)×(91/216)³(125/216)⁹)
=1-0.1828
=0.8172
