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neonofarm [45]
3 years ago
14

6 1/4 (x− 2/3 )=9 3/8 please help SOON

Mathematics
2 answers:
tester [92]3 years ago
8 0
The answer in improper fraction is 35/12 or in mixed number it’s in 2 11/12
Pie3 years ago
3 0

Answer:

x = 2 1/6

Step-by-step explanation:

6 1/4 (x− 2/3 )=9 3/8

Change the mixed numbers to improper fractions

6 1/4 = (4*6+1) / 4 = 25/4

9 3/8 = (8*9 +3) /8 = 75/8

25/4 (x-2/3) = 75/8

Multiply each side by 4/25

4/25*25/4 (x-2/3) = 75/8 *4/25

x-2/3 = 75/25 *4/8

x-2/3 = 3 *1/2

x-2/3 = 3/2

Add 2/3 to each side

x-2/3 +2/3 = 3/2 +2/3

x= 3/2 +2/3

Get a common denominator of 6

x  = 3/2 *3/3    + 2/3 *2/2

x = 9/6 + 4/6

x = 13/6

6 goes into 13 2 times with 1 left over

x = 2 1/6

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kotegsom [21]

Answer:

Note that PQ + QR = PR:

Once:  

PR = 15x-11\\PQ=3x+6

PQ + QR = PR\\\\(3x+6)+QR=(15x-11)\\\\QR=(15x-11)-(3x+6)\\\\QR=15x-11-3x-6\\\\QR=12x-17\\

Therefore, the answer is letter B

8 0
3 years ago
What is the area of the triangle?
fomenos

Answer:

1012.5

Step-by-step explanation:

5 0
3 years ago
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Dr. Jimenez found that after applying an antibiotic to bacteria, he observed only 90% of the bacteria left in the culture dish e
USPshnik [31]
<span>If the intial count was 100,000 bacteria, after one hour 90% decrease => 10 % stands => 100,000*0.1 bacetria. After two hours 90% decrease => 10% stands => 100,000*0.1^2. After three hours, they stand 100,000 * 0.1^3. After four hours, 100,000*0.1^4 and after five hours 100,000*0.1^5 = 1 bacteria. Answer: 1 bacteria. If the inital count is different you just have to muliply the inicial count time (0.1^n) to get the number of bacteria after n hours, and if the number of hours is 5, then the factor is (0.1^5). </span>
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3 years ago
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What is the circumference of a rectangle when the length is 8 inches and the width is 4 inches
Nikolay [14]
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5 0
3 years ago
The values of a sample statistic for different random samples of the same size from the same population will be the same.
Rus_ich [418]

Answer:

In general, sample statistics will tend to be different. With continuous random variables, this should always be the case (until rounding, which brings us back to "actually that's just theoretically continuous") and with discrete random variables this will often be the case with some statistics and perhaps more often not with others (how often it depends on the distribution pattern, sample size, and the particular statistics you are viewing).

Step-by-step explanation:

You can response your particular query by straight experiment, in simple cases.

For example, consider rolling a particular six-sided die (a well-made one that's very close to fair). You could withdraw two samples of some wanted size (n1 = 20

and n2 = 20 say) and calculate your sample statistics. I suggest you try it!

Actually, not being one to ask you to try something I wouldn't do myself, here are my attempts, first with one die (two samples each of size 20) and then a repeat with a different die:

Result of die A: 1 2 3 4 5 6

Sample 1 (Counts) 2 3 3 2 4 6

Sample 2 6 2 3 4 3 2

Result of die B: 1 2 3 4 5 6

Sample 1 (Counts) 3 7 3 0 3 4

Sample 2 1 4 1 5 4 5

And here are some summary statistics:

Die A Range median mean sd

Sample 1 5 4.5 4.05 1,791

Sample 2 5 3 3.10 1,774

Die B Median Mean Range SD

Sample 1 5 2.5 3.25 1,860

Sample 2 5  4  4.10 1,619

If you do, you will probably get the same maximum and minimum both times (I would expect both 1 and 6 to show in a sample of 20 about 95% of the time), but the means and standard deviations would be different.

The medians could be the same (about a 25% chance of that, with the usual definition of sample median even for n

), but easily not.

There is some chance of obtaining the same mean for two of these (because we are sampling a discrete distribution with only a few results), but there is a low probability of seeing it (around 3.7%);

You can also get the same standard deviation, but the chance is much less ... about 2/3 of a percentage.

At larger or smaller sample sizes, those possibilities change; and they change again if you extract from other distributions other than that of a (roughly) fair die.

That all those statistics I mentioned would be the same would be highly unlikely.

3 0
3 years ago
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