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Arte-miy333 [17]
3 years ago
14

NEED ANSWER IN LEAST THAN 3 Minutes

Mathematics
2 answers:
leonid [27]3 years ago
8 0
T<span>he next time all four supplies will arrive on the same day is in 24 weeks</span>
Anastasy [175]3 years ago
5 0
Shampoo: 2, 4, 6, 8, 10, 12, 14 16, 18 , 20, 22, 24
nail polish: 4, 8, 12, 16, 20,. 24
combs: 8, 16, 24
hair dryers, 12, 24

 find the least common multiple of the weeks given, 2, 4, 8, 12

 the number is 24 so every 24 weeks 




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The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x
Andrew [12]

Answer:

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}

The value of r is always between -1 \leq r \leq 1

And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

r^2 = 0.8^2 = 0.64

So then the best conclusion for this case would be:

c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.

Step-by-step explanation:

For this case we know that the correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. And we know that we use the height x of a child to predict the weight y of the child

We need to rememeber that the correlation is a measure of dispersion of the data and is given by this formula:

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}

The value of r is always between -1 \leq r \leq 1

And we have another measure related to the correlation coefficient called the R square and this value measures the % of variance explained between the two variables of interest, and for this case we have:

r^2 = 0.8^2 = 0.64

So then the best conclusion for this case would be:

c. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64.

3 0
3 years ago
Each tablet is 250 milligrams. Your doctor wants you to take 3 grams (g) per day. How many tablets do you need to take per day?
liraira [26]

Each tablet is 250 milligrams. Your doctor wants you to take 3 grams (g) per day

We know ,

1 gram = 1000 milligrams

250 milligrams makes 1 tablet

so 1000 milligrams makes how many tablets

\frac{1000}{250} = 4 tablets

1000 milligrams makes 4 tablets. That is 1 gram = 4 tablets

1 gram = 4 tablets

3 grams = 3 * 4 = 12 tablets

So you need to take 12 tablets per day.



4 0
3 years ago
Figure A is a scale image of figure B
serious [3.7K]
X=36

Divide the corresponding side (16) by 4/7
5 0
3 years ago
A store has shirts on display. Seven of the shirts are red. There are 5 more blue shirts than green shirts. There are 2 fewer ye
Nady [450]

Answer: green shirts = 6

Blue shirts = 11

Yellow shirts = 4

Red shirts = 7

Step-by-step explanation:

Red shirts = 7

Let green shirts be x.

There are 5 more blue shirts than green shirts. This means:

Blue shirts = x + 5

There are 2 fewer yellow shirts than green shirts. This means:

Yellow shirts = x - 2

There are 28 shirts in total

Red + blue + yellow + green = 28

7 + (x + 5) + (x - 2) + x = 28

7 + x + 5 + x - 2 + x = 28

10 + 3x = 28

3x = 28 - 10

3x = 18

x = 18/3

x = 6

There are 6 green shirts

Blue shirts = x + 5 = 6 + 5 = 11

Yellow shirts = x - 2 = 6 - 2 = 4

Red shirts = 7

4 0
2 years ago
Nielsen ratings are based on televisions in 50005000 households. Nielsen estimates that 12 comma 00012,000 people live in these
avanturin [10]

Answer:

We are 95% confident that the true proportion of TV audience is between 65.15% and 65.85%

Step-by-step explanation:

-From the given information, \hat p=0.65.

-We calculate the confidence interval using this value at 95% confidence level:

CI=\hat p\pm z \sqrt{\frac{\hat p(1-\hat p)}{n}}\\\\\\=0.65\pm 1.96\times \sqrt{\frac{0.65\times 0.35}{12000}}\\\\\\=0.65\pm 0.0085\\\\\\=[0.6415,0.6585]

So, the 95% confidence interval is (0.6515,0.6585).

Hence, we are 95% confident that the true proportion of TV audience is between 65.15% and 65.85%.

6 0
3 years ago
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