Without the actual numeric data coordinates, it is impossible to compute the true r value. Though we can estimate. The data points are negatively correlated in a fairly strong manner. We can draw a straight line close to all of these points, so the r value is going to be fairly close to -1. The closer r is to -1, the stronger the negative correlation. Having r = -1 exactly means all of the points fall on some single straight line that slopes downward.
Choice B is the next best choice, but its correlation isn't as strong. So that's why I ruled it out. Choices C and D are ruled out immediately since they are positive values.
Answer:
B. $213.30
Step-by-step explanation:
Mean amount spent on Christmas gifts = Σx / n
Where,
Σ= sum of
x= cost of each Christmas gifts
n= number of Christmas gift
Mean amount spent on Christmas gifts = Σx / n
= ( $178.622 + $247.583 + $228.454 + $176.645 + $180.226 + $268.45 ) / 6
= $1,279.98 / 6
= $213.33
Round to the nearest cent
= $213.30
Option b is the correct answer
The mean amount spent by six college buddies on Christmas gifts, They spent: approximately $213.33 when rounded to the nearest cent.
The process is quite straightforward and involves the principles of statistics, particularly the calculation of the arithmetic mean. Here are the steps we can follow to solve this problem:
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B. 8c – 2
C. 4c + 6
D. 4c – 2
Answer:
A. 8c+2 that's the answer srr if it's not
Answer:
P2 affirms P1 and the conclusion is in the same direction.
P1--->P2--->C
This argument is valid.
Step-by-step explanation: using the syllogism rules.
Premises 1 (P1) = Some foreign emissaries are persons without diplomatic immunity,
Premises 2 (P2) = so some persons invulnerable to arrest and prosecution are foreign emissaries
Conclusion (C) = because no persons with diplomatic immunity are persons vulnerable to arrest and prosecution.
From the argument:
P1 uses "some", that means it's not "all" foreign emissaries person that does not have diplomatic immunity. This means that some other foreign emissaries have diplomatic immunity
P2 uses "some", that means it's affirms to that part of P1 which states that some foreign emissaries have diplomatic immunity.
The conclusion is valid because the part of P2 which states that some foreign emissaries are vulnerable to arrest, which affirms with P1 which states that Some foreign emissaries are persons without diplomatic immunity. That means no persons with diplomatic immunity are persons vulnerable to arrest and prosecution. This conclusion literally means that if you don't have diplomatic immunity, you are vulnerable to arrest and prosecution.
Therefore;
P2 affirms P1 and the conclusion is in the same direction.
P1--->P2--->C
This argument is valid.
in the bank until it reaches 9600 dollars?
Answer:
14.4
Step-by-step explanation:
Given that :
Principal = 4000
Interest (r) = 6.25% compounded annually
Calculate time, t, if final amount A = 9600
Using the compound interest formula :
A = P(1 + r/n)^n*t
A = final amount
n = number of times interest is applied per period
9600 = 4000(1 + 0.0625)^t
9600 = 4000(1.0625)^t
9600/4000 = 1.0625^t
2.4 = 1.0625^t
Take the log of both sides
0.3802112 = 0.0263289t
t = 0.3802112/0.0263289
t = 14.440811
t = 14.4 ( nearest tenth)
Let X be the number of female employee. Let n be the sample size, p be the probability that selected employee is female.
It is given that 45% employee are female it mean p=0.45
Sample size n=60
From given information X follows Binomial distribution with n=50 and p=0.45
For large value of n the Binomial distribution approximates to Normal distribution.
Let p be the proportion of female employee in the given sample.
Then distribution of proportion P is normal with parameters
mean =p and standard deviation =
Here we have p=0.45
So mean = p = 0.45 and
standard deviation =
standard deviation = 0.0642
Now probability that sample proportions of female lies between 0.40 and 0.55 is
P(0.40 < P < 0.45) =
= P(-0.7788 < Z < 1.5576)
= P(Z < 1.5576) - P(Z < -0.7788)
= P(Z < 1.56) - P(Z < -0.78)
= 0.9406 - 0.2177
= 0.7229
The probability that the sample proportion of females is between 0.40 and 0.55 is 0.7229
To find the probability that the sample proportion of females is between 0.40 and 0.55, convert the sample proportions to z-scores and use the z-table to find the probabilities.
To find the probability that the sample proportion of females is between 0.40 and 0.55, we need to find the z-scores associated with these proportions and use the z-table to find the probabilities.
First, we need to convert the sample proportions to z-scores using the formula: z = (p - P) / √(P(1-P) / n), where p is the sample proportion, P is the population proportion, and n is the sample size.
Once we have the z-scores, we can use the z-table to find the probabilities. The probability that the sample proportion of females is between 0.40 and 0.55 is the difference between the probabilities associated with the z-scores for 0.40 and 0.55.
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