Answer:
4,200
Step-by-step explanation:
Answer:
<em><u>T</u></em><em><u>H</u></em><em><u>E</u></em><em><u> </u></em><em><u>C</u></em><em><u>O</u></em><em><u>R</u></em><em><u>R</u></em><em><u>E</u></em><em><u>C</u></em><em><u>T</u></em><em><u> </u></em><em><u>A</u></em><em><u>N</u></em><em><u>S</u></em><em><u>E</u></em><em><u>R</u></em><em><u> </u></em><em><u>O</u></em><em><u>F</u></em><em><u> </u></em><em><u>T</u></em><em><u>H</u></em><em><u>I</u></em><em><u>S</u></em><em><u> </u></em><em><u>Q</u></em><em><u>U</u></em><em><u>E</u></em><em><u>S</u></em><em><u>T</u></em><em><u>I</u></em><em><u>O</u></em><em><u>N</u></em><em><u> </u></em><em><u>I</u></em><em><u>S</u></em><em><u> </u></em><em><u>5</u></em><em><u>.</u></em>
Step-by-step explanation:
Here,
a23=6
a12=5
a32=6
Now,
a23+a12-a32
=6+5-6
=5

B is true for both inequalities.
Answer:
555.56
Step-by-step explanation:
Purpose of the study: To determine if women are better drivers than men.
Survey or Opinion population: 1,000
You are experimenting on 9 out of a thousand opinions.
5 of these opinions are that women are better drivers
4 of these opinions are that women are not better drivers
You want to know the <em>sample</em> (full sample size is 9) <em>proportion</em> for women as better drivers; using the large sample method. This method is also called the asymptotic method.
This involves approximating the desired statistic, with just a small fraction of the population; in this case, 9/1000.
This approximation will get more and more accurate as sample size increases and you know that a larger sample size gives a better representation and interpretation of the population preference!
So using ratio, the sample proportion for women as the better drivers is given by:
5/9 x 1000 = 555.56 opinions
<h2>
Answer:</h2>
A)
Mean for:
Sample Z -- 447.5
Sample Y-- 409.3
B)
Sample Y has larger deviation from the mean.
<h2>
Step-by-step explanation:</h2>
Z Plots Y Plots
456 395
454 390
449 391
453 402
431 395
456 405
445 432
430 438
463 420
438 425
A)
For sample Z--
The mean is calculated by:
Ratio of sum of all the data points of Z-sample to the total number of points i.e. 10.

Similarly for sample Y--
The mean is calculated as follows:

B)
As we could see that the data Y has a greater spread from the mean as compared to the sample Z.
As all the points in the sample Z are close to the mean and have less spread.
The standard deviation is most commonly used to measure the spread of the data.
Standard deviation of sample Z is: 10.651
Standard deviation of sample Y is: 16.9944
Hence Sample Y have larger deviation from the mean.