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netineya [11]
3 years ago
11

Explain how the cartons and boxes for table tennis balls are like the digits for numbers in our base-10 number system.

Mathematics
2 answers:
Helga [31]3 years ago
5 0

Answer:

Base 10 Number System = (0,1,2,3,4,5,6,7,8,9)

In a  Carton of table tennis there are  10 boxes.

And Each Box can Hold 10 Balls.and if i mark boxes from 0 to 9, then

then there are 10 boxes , Total number of Balls=100

So if I represent a single Carton by A, then

A[single carton] ={0,1,2,3,4,5,6,7,8,9}= 10 boxes =100 balls

B [2 carton]= 20 boxes=200 balls

C[ 5 cartons + 3 Boxes] = 5× 100+ 3×10 =530 balls

D[ 12 cartons + 8 Boxes]= 12×100+8×10=1280 balls

Now you can see,

Each carton is holding the balls  in decimal number system.

Boxes = Ten's place in number system,

Number of cartons = either Hundred place or thousand place or more than that

In this way we can represent Carton and Box for table tennis balls in decimal number system having base 10 .

 




AysviL [449]3 years ago
3 0

Answer:

To explain the cartoons and the boxes for table tennis balls are like the digits for numbers in base-10 number system

Here we know that, the number of table tennis balls in one box =10 balls

and the number of table tennis balls in boxes in each cartoon = 10 balls

Therefore, The number of table tennis balls in each cartoon =10×10=100 balls

Hence for the number of balls ,the hundreds place tells the number of cartoons and  tens place tells the number of boxes which left as remainder or without cartoon.


For example if the total tennis balls =540 then its hundreds place i.e 5 tells the number of cartoons and its tens place i.e.4 tells the number of boxes which left as remainder or without cartoon.


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Answer:

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

z=\frac{0.6-0.2}{\sqrt{0.4(1-0.4)(\frac{1}{50}+\frac{1}{50})}}=4.082    

p_v =2*P(Z>4.082)=4.46x10^{-5}  

So the p value is a very low value and using any significance level for example \alpha=0.05 always p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion 1 is significantly different from proportion 2.

Step-by-step explanation:

1) Data given and notation  

X_{1}=30 represent the number of people with a characteristic in 1

X_{2}=10 represent the number of people with a characteristic in 2

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n_{2}=50 sample of 2 selected  

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We need to conduct a hypothesis in order to check if the proportion 1 is different from proportion 2 , the system of hypothesis would be:  

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

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z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}   (1)  

Where \hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{30+10}{50+50}=0.4  

3) Calculate the statistic  

Replacing in formula (1) the values obtained we got this:  

z=\frac{0.6-0.2}{\sqrt{0.4(1-0.4)(\frac{1}{50}+\frac{1}{50})}}=4.082    

4) Statistical decision

For this case we don't have a significance level provided \alpha, but we can calculate the p value for this test.    

Since is a two sided test the p value would be:  

p_v =2*P(Z>4.082)=4.46x10^{-5}  

So the p value is a very low value and using any significance level for example \alpha=0.05 always p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion 1 is significantly different from proportion 2.  

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