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never [62]
3 years ago
5

On a backpacking trip through Europe, Troy spent 20 Swiss francs to stay one night in a youth hostel. If the foreign exchange ra

te between the U.S. dollar and the Swiss franc is 1:2.2, how much did Troy spend in U.S. dollars?
Mathematics
2 answers:
Vlad [161]3 years ago
5 0
He spent 9 dollars and 9 cents so $9.09
mina [271]3 years ago
4 0

Answer:

Troy spent $9.09.

Step-by-step explanation:

Troy spent 20 Swiss Francs to stay one night in a youth hostel.

1 U.S. Dollar = 2.2 Swiss franc

We have to convert 20 Swiss franc to U.S. dollars.

So we divide 20 by 2.2 to convert Swiss franc to U.S. dollars.

= \frac{20}{2.2} = 9.09090909 ≈ $9.09

Troy spent $9.09 to stay one night in a youth hostel.

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4. Assume that the chances of a basketball player hitting a 3-pointer shot is 0.4 and the probability of hitting a free-throw is
vovikov84 [41]

Answer:

0.0334 = 3.34% probability that the player will make exactly 3 3-pointers and 5-free throws.

Step-by-step explanation:

For each 3-pointer shot, there are only two possible outcomes. Either the player makes it, or the player does not. The same is valid for free throws. This means that both the number of 3-pointers and free throws made are given by binomial distributions.

Since 3-pointers and free throws are independent, first we find the probability of making exactly 3 3-pointers out of 10, then the probability of making exactly 5 free throws out of 10, and then the probability that the player will make exactly 3 3-pointers and 5-free throws is the multiplication of these probabilities.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

C_{n,x} = \frac{n!}{x!(n-x)!}

And p is the probability of X happening.

Probability of making 3 3-pointers out of 10:

The chances of a basketball player hitting a 3-pointer shot is 0.4, which means that p = 0.4. So this is P(X = 3) when n = 10.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 3) = C_{10,3}.(0.4)^{3}.(0.6)^{7} = 0.21499

Probability of making 5 free throws out of 10:

The probability of hitting a free-throw is 0.65, which means that p = 0.65. The probability is P(X = 5) when n = 10.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 3) = C_{10,5}.(0.65)^{5}.(0.35)^{5} = 0.15357

Calculate the probability that the player will make exactly 3 3-pointers and 5-free throws.

0.21499*0.15537 = 0.0334

0.0334 = 3.34% probability that the player will make exactly 3 3-pointers and 5-free throws.

5 0
3 years ago
What is the distance between the points 4 and -5 on a number line?
Ket [755]

Answer:

9

4--3--2--1--0--1--2--3--4--5

Positive        Negative

Step-by-step explanation:

6 0
3 years ago
Which shows the correct way to use the rule ""multiply by the reciprocal"" for the expression below? 7 divided by StartFraction
guajiro [1.7K]

Given:

The expression is \dfrac{7}{\frac{5}{8}}.

To find:

The shows the correct way to use the rule ""multiply by the reciprocal"" for the given expression.

Solution:

According to the rule "multiply by the reciprocal", if a,b,c,d are four number, then

\dfrac{\dfrac{a}{b}}{\dfrac{c}{d}}=\dfrac{a}{b}\times \dfrac{d}{c}

We have,

\dfrac{7}{\frac{5}{8}}

It can be written as

\dfrac{7}{\frac{5}{8}}=\dfrac{\dfrac{7}{1}}{\dfrac{5}{8}}

Using the rule "multiply by the reciprocal", we get

\dfrac{\dfrac{7}{1}}{\dfrac{5}{8}}=\dfrac{7}{1}\times \dfrac{8}{5}

\dfrac{\dfrac{7}{1}}{\dfrac{5}{8}}=\dfrac{7\times 8}{1\times 5}

\dfrac{\dfrac{7}{1}}{\dfrac{5}{8}}=\dfrac{56}{5}

Therefore, the correct option is D.

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3 years ago
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Given WXYZ what is the measure of Z
nekit [7.7K]

Answer: 35

Step-by-step explanation:

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A set of bivariate data was used to create a least squares regression line. Which of the following is minimized by the line
77julia77 [94]

Answer:

B) The sum of the squared residuals

Step-by-step explanation:

Least Square Regression Line is drawn through a bivariate data(Data in two variables) plotted on a graph to explain the relation between the explanatory variable(x) and the response variable(y).

Not all the points will lie on the Least Square Regression Line in all cases. Some points will be above line and some points will be below the line. The vertical distance between the points and the line is known as residual. Since, some points are above the line and some are below, the sum of residuals is always zero for a Least Square Regression Line.

Since, we want to minimize the overall error(residual) so that our line is as close to the points as possible, considering the sum of residuals wont be helpful as it will always be zero. So we square the residuals first and them sum them. This always gives a positive value. The Least Square Regression Line minimizes this sum of residuals and the result is a line of Best Fit for the bivariate data.

Therefore, option B gives the correct answer.

5 0
3 years ago
Read 2 more answers
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