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KiRa [710]
3 years ago
11

Ice thickness decreases at a rate of 0.2 meters per week. After 7 weeks,the ice is only 2.4 meters thick. What is the equation f

or relationship between the thickness and the number of weeks?
Mathematics
1 answer:
sergiy2304 [10]3 years ago
7 0

Answer:

The equation for relationship between the thickness and the number of weeks is f(x)=3.8 -0.2*x

Step-by-step explanation:

Ice thickness decreases at a rate of 0.2 meters per week. This can then be represented by the expression

f(x) = k - 0.2*x

where k is the thickness of the ice before the melting starts and x is the number of weeks.

After 7 weeks, the ice is only 2.4 meters thick. This means that x has a value of 7, while f (7) = 2.4. Replacing in the previous expression:

2.4=k -0.2*7

and solving you get:

2.4=k- 1.4

2.4 + 1.4= k

3.8= k

Then, <u><em>the equation for relationship between the thickness and the number of weeks is f(x)=3.8 -0.2*x</em></u>

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The length of a swimming poollane
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8 0
3 years ago
what is the volume of the hamsta snack box with a width of 1 1/2 inches, a length of2 1/2 inches, and a height of 4 inches
jenyasd209 [6]

<u>Given:</u>

The width of the snack box is 1 \frac{1}{2} \ inches=\frac{3}{2} \ inches

The length of the snack box is 2 \frac{1}{2} \ inches=\frac{5}{2} \ inches

The height of the snack box is 4 inches.

We need to determine the volume of the hamsta snack box.

<u>Volume of the box:</u>

The volume of the box can be determined using the formula,

V=L \times W \times H

where L is the length, W is the width and H is the height of the box.

Substituting the values, we get;

V=4 \times \frac{3}{2} \times \frac{5}{2}

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3 0
3 years ago
. Suppose (as is roughly true) that 88% of college men and 82% of college women were employed last summer. A sample survey inter
denis23 [38]

Answer:

(a) The approximate distribution of the proportion pf of women who worked = 0.82, the standard distribution = 0.00738

The approximate distribution of the proportion pM of men who worked = 0.88, the standard distribution ≈ 0.01625

(b)  pM - pF =  0.06

While pF - pM = -0.06

The difference in the standard deviation ≈ 0.01025

(c) The probability that a higher proportion of women than men worked last year is 0

Step-by-step explanation:

(a) The given information are;

The percentage of college men that were employed last summer = 88%

The percentage of college women that were employed last summer = 82%

The number of college men interviewed in the survey = 400

The number of college women interviewed in the survey = 400

Therefore, given that the proportion of women that worked = 0.82, we have for the binomial distribution;

p = 0.82

q = 1 - 0.82 = 0.18

n = 400

Therefore;

p × n = 0.82 × 400 = 328 > 10

q × n = 0.18 × 400 = 72 > 10

Therefore, the binomial distribution is approximately normal

We have;

The \  mean = p = 0.82\\\\The \ standard \ deviation, \sigma  = \sqrt{ \dfrac{p \times q}{{n} } }= \sqrt{ \dfrac{0.82 \times 0.18}{{400} }} \approx  0.01921\\

Therefore, the approximate distribution of the proportion pf of women who worked = 0.82, the standard distribution ≈ 0.01921

Similarly, given that the proportion of male that worked = 0.88, we have for the binomial distribution;

p = 0.88

q = 1 - 0.88 = 0.12

n = 400

Therefore;

p × n = 0.88 × 400 = 352 > 10

q × n = 0.12 × 400 = 42 > 10

Therefore, the binomial distribution is approximately normal

We have;

The \  mean = p = 0.88\\\\The \ standard \ deviation, \sigma  = \sqrt{ \dfrac{p \times q}{{n} } }= \sqrt{ \dfrac{0.88 \times 0.12}{{400} }} \approx  0.01625\\

Therefore, the approximate distribution of the proportion pM of men who worked = 0.88, the standard distribution ≈ 0.01625

(b) Given two normal random variables, we have

The distribution of the difference the two normal random variable = A normal random variable

The mean of the difference = The difference of the two means = pM - pF = 0.88 - 0.82 = 0.06

While pF - pM = -0.06

The difference in the standard deviation, giving only the real values, is given as follows;

The \ difference \ in \ standard \ deviation  = \sqrt{ \dfrac{p_1 \times q_1}{{n_1} } -\dfrac{p_2 \times q_2}{{n_2} } }\\\\= \sqrt{\dfrac{0.82 \times 0.18}{{400} }-\dfrac{0.88 \times 0.12}{{400} }} \approx  0.01025\\

(c) When there is no difference between the the proportion of men and women that worked last summer, the probability that there is a difference = 0

Therefore, taking 0 as the standard score, we have;

z = \dfrac{0 - (-0.06)}{0.01025}  \approx 5.86

Given that the maximum values for a cumulative distribution table is approximately 4, we have that the probability that a higher proportion of women than men worked last year is 0.

3 0
3 years ago
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