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Mazyrski [523]
3 years ago
10

Oliver works at a book store.He packed 20 identical paperbacks and 9 identical textbooks in a box .The total mass of the book wa

s 44.4 pounds . After he put 1 more textbook and 5 more paperbacks in the box,the total mass of the books was 51 pounds.
Mathematics
1 answer:
Natasha_Volkova [10]3 years ago
7 0
Let x be the mass of the paperbacks and y be the mass of the textbook.

20x + 9y = 44.4 ----------- (1)
25x + 10y = 51 -------------(2)

(1) x 10:
200x + 90y = 444 --------(1a)

(2) x 9:
225x + 90y = 459 --------(2a)

(2a) - (1a):
25x = 15
x = 0.6 -------- sub into (1)

20 (0.6) + 9y = 44.4
12 + 9y = 44.4
9y = 44.4 - 12
9y = 32.4
y = 3.6 

So the paperback's mass is 0.6 pounds and textbook is 3.6 pounds




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A graduate student is designing a research study. She is hoping to show that the results of an experiment are statistically sign
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1 year ago
Suppose that administrators at a large urban high school want to gain a better understanding of the prevalence of bullying withi
boyakko [2]

Answer:

lower limit =0.261

upper limit =0.369

Step-by-step explanation:

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".  

The margin of error is the range of values below and above the sample statistic in a confidence interval.  

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

Description in words of the parameter p

p represent the real population proportion of people that have experienced bullying

X= 63 people in the random sample that have experienced bullying

n=200 is the sample size required  

\hat p=\frac{63}{200}=0.315 represent the estimated proportion of people that have experienced bullying

z_{\alpha/2} represent the critical value for the margin of error  

The population proportion have the following distribution  

p \sim N(p,\sqrt{\frac{p(1-p)}{n}})

Numerical estimate for p

In order to estimate a proportion we use this formula:

\hat p =\frac{X}{n} where X represent the number of people with a characteristic and n the total sample size selected.

\hat p=\frac{63}{200}=0.315 represent the estimated proportion of people that they were planning to pursue a graduate degree

Confidence interval

The confidence interval for a proportion is given by this formula  

\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}  

For the 90% confidence interval the value of \alpha=1-0.90=0.1 and \alpha/2=0.05, with that value we can find the quantile required for the interval in the normal standard distribution.  

z_{\alpha/2}=1.64  

And replacing into the confidence interval formula we got:  

0.315 - 1.64 \sqrt{\frac{0.315(1-0.315)}{200}}=0.261  

0.315 - 1.64 \sqrt{\frac{0.315(1-0.315)}{200}}=0.369  

And the 90% confidence interval would be given (0.261;0.369).  

We are confident at 90% that the true proportion of people that they were planning to pursue a graduate degree is between (0.261;0.369).  

lower limit =0.261

upper limit =0.369

5 0
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Juli2301 [7.4K]

Luis sold 148 TVs.

Step-by-step explanation:

163-15=148

3 0
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