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SOVA2 [1]
3 years ago
14

will the contents of a cylindrical can of soup with a 1.5-inch radius and a 5-inch height fit into a pan with a 4-inch radius an

d 3-inch height?
Mathematics
1 answer:
Anna007 [38]3 years ago
3 0

Answer:

Answer: The volume of the soup can is less that that of the pan, so the soup will fit in the pan.

Step-by-step explanation:

a. V = s3

V = (7 km)3

V = 7 km × 7 km × 7 km

V = 343 km3

b. V = s3

V = (11 yd.)3

V = 11 yd. × 11 yd. × 11 yd.

V = 1,331 km cu. yd.

a. V = l × w × h

V = 6 m × 2 m × 3 m

V = 36 m3

b. V = l × w × h

V = 5 ft. × 10 ft. × 8 ft.

V = 400 cu. ft.

a. V = πr2h

V = 3.14 × (3 in.)2 × 3 in.

V = 3.14 × 9 sq. in. × 3 in.

V = 84.78 cu. in.

b. V = πr2h

V = 3.14 × (1 m)2 × 4 m

V = 3.14 × 1 m2 × 4 m

V = 12.56 m3

V = s3

V = (2 ft.)3

V = 2 ft. × 2 ft. × 2 ft.

V = 8 cu. ft.

Answer: The capacity of the ice chest is 8 cubic feet.

V = πr2h

V = 3.14 × (1 ft.)2 × 3 ft.

V = 3.14 × 1 sq. ft. × 3 ft.

V = 9.42 cu. ft.

Answer: The volume of the trash can is 9.42 cubic feet.

Closet #1

V = l × w × h

V = 4 ft. × 5 ft. × 8 ft.

V = 160 cu. ft.

Closet #2

V = l × w × h

V = 6 ft. × 3 ft. × 8 ft.

V = 144 cu. ft.

Compare the size of the closets

160 cu. ft. > 144 cu. ft.

Answer: The first closet is larger.

Both the can and the pan are cylindrical shapes. Compare the volumes of the two objects.

Volume of Can

V = πr2h

V = 3.14 × (1.5 in.)2 × 5 in.

V = 3.14 × 2.25 sq. in. × 5 in.

V = 35.325 cu. in.

Volume of Pan

V = πr2h

V = 3.14 × (4 in.)2 × 3 in.

V = 3.14 × 16 sq. in.× 3 in.

V = 150.72 cu. in.

35.325 cu. in. soup can < 150.72 cu. in pan

Answer: The volume of the soup can is less that that of the pan, so the soup will fit in the pan.

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The option C) y = 15/x

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b) is an example of linear variation (it is the equation of a straight line that does not pass through the origin)

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Answer:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

Step-by-step explanation:

Linear regression is a way "to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables)".

Regression estimates are "used to describe data and to explain the relationship between one dependent variable and one or more independent variables"

The linear model is given by the following equation Y=mx +b, where y is the dependent variable, x the independent variable, m the slope and b the intercept.

For this case we have the following info given:

\sum_{i=1}^n (x_i -\bar x)^2 =98775

\sum_{i=1}^n (y_i -\bar y)^2 =19.4

\bar x =26.36

\bar y =0.5188

n= 40  represent the sample size

\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y) =796.94

The total sum of squares is given by this formula:

SST= \sum_{i=1}^n (y_i -\bar y)^2 =19.4

And from the formulas for a simple regression, we need to calculate the slope for the regression like this:

m=\frac{\sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)}{\sum_{i=1}^n (x_i -\bar x)^2}

And if we replace the values given we have:

m=\frac{796.94}{98775}=0.008068

We have another useful equation in order to find the sum of squares for the regression, given by:

SSR=m* \sum_{i=1}^n (x_i -\bar x)(y_i -\bar y)=0.008068*796.94=6.430

And we know this equivalence:

SST= SSR+SSE

And solving for the sum of squares for the error we have:

SSE=SST-SSR=19.4-6.430=12.97

So then we have the final solutions:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

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