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2 years ago

Divide. 8,375 ÷ 45 number and remainder

Mathematics

1 answer:

Darina [25.2K]2 years ago

4 0

Answer: 186 with a remainder of 5.

Method One:

See attached for my work, I used long divison.

Method Two:

We will use a calculator to find the value, then multiply the value (without the decimals) by the divisor. Lastly, we will subtract. This makes more sense with the work:

8,375 ÷ 45 = 186.11111111

186 * 45 = 8,370

8,375 - 8,370 = 5

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Given N(14, 3)

bearhunter [10]

Answer:

Step-by-step explanation:

we would apply the formula for normal distribution which is expressed as

z = (x - µ)/σ

Where

x = variable

µ = mean output

σ = standard deviation

From the information given,

µ = 14

σ = 3

1) P(x < 20)

For x = 20,

z = (20 - 14)/3 = 2

From the normal distribution table, the corresponding probability value is 0.98

% = 0.98 × 100 = 98%

2) P(11 ≤ x ≤ 17)

For x = 11,

z = (11 - 14)/3 = - 1

From the normal distribution table, the corresponding probability value is 0.16

For x = 17,

z = (17 - 14)/3 = 1

From the normal distribution table, the corresponding probability value is 0.84

P(11 ≤ x ≤ 17) = 0.84 - 0.16 = 0.68

% = 0.68 × 100 = 68%

3) P(x > 14) = 1 - P(x ≤ 14)

For x = 14,

z = (14 - 14)/3 = 0

From the normal distribution table, the corresponding probability value is 0.5

P(x > 14) = 1 - 0.5 = 0.5

% = 0.5 × 100 = 50%

4) P(5 ≤ x ≤ 17)

For x = 5,

z = (5 - 14)/3 = - 3

From the normal distribution table, the corresponding probability value is 0.00135

For x = 17,

z = (17 - 14)/3 = 1

From the normal distribution table, the corresponding probability value is 0.84

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% = 0.839 × 100 = 83.9%

7 0

4 years ago

You walk 20 meters north, then 5 meters south. what is your displacement?

Viktor [21]

Sry this is completely off topic, but where do you go to ask questions? I can't seem to find it. The answer is C I think

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3 years ago

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jeyben [28]

Answer:

The correct option is (A).

Step-by-step explanation:

The multiple linear regression equation is given by, $y=\alpha +\beta _{1} x_{1}+\beta _{2}x_{2}$ , where α = constant and β $_{i}$ = slope coefficients of regression line.

To test if there is a important relationship amid X $_{i}$ and Y, we use the t-statistic test.

The t-statistic for regression coefficient analysis is given by,

$t=\frac{\beta_{i}}{S.E._{\beta_{i}}}$

The regression equation for test scores dependent upon the two explanatory variables, the student-teacher ratio and the percent of English learners is:

$\text{TestScore} = 698.9 - 1.10 \text{ STR} - 0.650 \text{ PctEL}$