A man walks a certain distance due North and then the same distance plus a further 7 km due East. If the final distance from the starting point 17 km, find the distances he walks North and East​

Answer:

B

Step-by-step explanation:

the equal is correctly

3x + 1 = 2x + 4

what was done now :

2 x-blocks (2x) subtracted from the right side, and 1 numbered block subtracted from the left side.

to reestablish balance and equality of both sides, we need to do more the exact same things - just in the other sides.

2 x-blocks subtracted from the LEFT side, and 1 numbered block subtracted from the RIGHT side.

and that is answer B.

Answer:

-4.23230, -4.232300, -4.2323000

Answer:

1) -4.23230 2)-4.232300 3)-4.2323000

Step-by-step explanation:

Where is my brainliest and my points :)

Answer:

27

12

3

0

3

12

27

Step-by-step explanation:

y=3x^2

JUST PLUG IN X

Answer:

1.4 people out of 10

Step-by-step explanation:

Just divide it by 10

Answer:

only 4 people

The probability that next ice cream cone sold is a chocolate chip ice cream cone is 0.052. The result is obtained by dividing the chocolate chip ice cream cone sold by the total ice cream from the previous week data.

Probability is a numerical description of how possible an event to happen. Probability of an event can be expressed as

P(A) = n(A) / n(S)

Where

The previous week data shows that

To estimate the probability that will happen in the future, we use the data happened in the past.

The probability that the ice cream cone sold for chocolate chip variant is

P(A) = n(A) / n(S)

P(A) = 52 / 997

P(A) = 0.052

Hence, the probability of next selling a chocolate chip ice cream cone is 0.052.

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Answer: 52/997

Step-by-step explanation: I checked on khan

The smallest positive integer n will be 10 .

To find : the smallest positive integer n such that the rightmost digits of  n ! and ( n + 1 ) ! are same .

Since ,

putting n = 10 gives

n ! = 10 ! = 3628800

and ( n + 1 ) ! = 39916800

Last three digits ( rightmost digits ) ie. 800 are same .

Hence , n = 10 is the required answer ,

Therefore , the smallest positive integer is n = 10 such that the rightmost digits of  n ! and ( n + 1 ) ! are same .

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you can reduce it to factors of degree 2 or less).

The two dice do not need to be identical. If it is possible, do it. If it is not possible, prove that it is not possible.

Some hints I got were to try to construct a pair of nonstandard dice such that the generating function for their sum matches the corresponding g.f. for a pair of standard dice and to note that the g.f. for a pair of standard dice can be factored quite a bit (you can reduce it to factors of degree 2 or less).

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a) The probability of both balls drawn from the bag be red is 6/55

b) The probability of one ball red and other ball black is 4/11

Given,

Number of white balls in the bag = 2

Number of red balls in the bag = 4

Number of black balls in the bag = 5

Two balls are drawn from the bag.

Here,

a) Find the probability of both balls be red.

(²C₀ x ⁴C₂ x ⁵C₀) / ¹¹C₂

= (1 x 6 x 1)/ 55

= 6/55

That is,

The probability of both balls be red is 6/55

b) Find the probability of one ball red and other ball black

(²C₀ x ⁴C₁ x ⁵C₁) / ¹¹C₂

= (1 x 4 x 5) / 55

= 20/55

= 4/11

That is,

The probability of one ball red and other ball  black is 4/11

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Answer:

a.) c(t)=44t+48

b.) the total initial cost of setting up a website and maintaining it for 6 months is $312

Step-by-step explanation:

h

If 18% of the pieces in the box were unpainted, that means 82% of the pieces in the box were painted.

And since 738 pieces were painted, that number comprises 82% of the total number of pieces.

Therefore, the number of pieces in the box was : 738 : 82% = 900 (pieces)

Answer:

57

Step-by-step explanation:

10% of 570 = 57 (dividing by 10). Times that by 3, which is 171. Now divide 171 by 3, equals 57 (the answer).

a) No, p1 = 20, p2 = 19.50 is not a Nash Equilibrium.

b) Yes, there is a Nash Equilibrium in which Firm 2 makes a positive profit.

c) Player 1 has infinitely many strategies.

d) Yes, p1 = 15, p2 = 15 is a Nash Equilibrium.

e) No, p1 = 21, p2 = 21 is not a Nash Equilibrium.

Nash Equilibrium is a state of a strategic game where no player has an incentive to deviate from his or her chosen strategy after considering the strategies of other players. A game has more than one Nash equilibrium if players are unable to agree on a cooperative strategy to play.

Finding Nash Equilibrium

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a) The recurrence T(n) = T(n/2) + 1 has an asymptotic complexity of O(log(n)).   b) The recurrence T(n) = 2T(n/2) + n has an asymptotic complexity of Ω(nlog(n)).



a) To analyze the recurrence T(n) = T(n/2) + 1, we make a guess that T(n) = O(log(n)). Assuming this guess is correct, we substitute T(n/2) with O(log(n/2)) = O(log(n)) in the recurrence relation. We get T(n) = O(log(n)) + 1. Since O(log(n)) + 1 is dominated by O(log(n)), our guess holds true, and we conclude that T(n) = O(log(n)).

b) For the recurrence T(n) = 2T(n/2) + n, we make a guess that T(n) = Ω(nlog(n)). Assuming this guess is correct, we substitute T(n/2) with Ω((n/2)log(n/2)) = Ω(nlog(n) - nlog(2)) in the recurrence relation. We get T(n) = Ω(nlog(n) - nlog(2)) + n. Simplifying, we have T(n) = Ω(nlog(n) + n - nlog(2)). Since nlog(n) dominates nlog(2), T(n) is Ω(nlog(n)), confirming our guess.

In both cases, the substitution validates our initial guesses for the asymptotic complexity of the recurrences.Therefore, The recurrence T(n) = T(n/2) + 1 has an asymptotic complexity of O(log(n)).   The recurrence T(n) = 2T(n/2) + n has an asymptotic complexity of Ω(nlog(n)).

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Using the box-whisker plot approach, it is computed that 50% of the data values are more than 45.

In a box-whisker plot, as seen in the illustration, The minimum, first quartile, median, third quartile, and maximum quartiles are shown by a rectangular box with two lines and a vertical mark. In descriptive statistics, it is employed.

Given the foregoing, the box-whisker plot depicts a specific collection of data. A vertical line next to the number 45 shows that it is the 50th percentile in this instance and that 45 is the median of the data.

It indicates that 50% of the values are higher than 45 and 50% of the values are higher than 45.

Using this technique, we can easily determine the proportion of data for which the value is higher or lower. Data analysis and result interpretation are aided by it. Therefore, 50% of values exceed 45.

Note: The correct question would be as

The box-and-whisker plot below represents some data sets. What percentage of the data values are greater than 45?

0

H

10

20

30 40

50 60

70 80 90 100

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74=p×38 is the percent equation that can be used to solve the following problem 38 What's is the percent of 74

To find the percent of a number, we need to divide the part (38) by the whole (74) and then multiply by 100 to convert the decimal to a percentage.

So the percent equation is:

38/74 = p/100

We can cross-multiply to solve for p:

74p = 38 × 100

p = (38 × 100) / 74

p = 51.35

Therefore, the percent of 38 in 74 is approximately 51.35%, option B is correct

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Answer:

Increase: $6,844

New Price: $64,844

Step-by-step explanation:

58,000x.118=6844

58000+6844=64844

A rectangle contains the area of 60 inch² then the dimension is as follows:

length × width

60 × 1

30 × 2

20 × 3

15 × 4

12 × 5

10 × 6

The square inch unit provides the area. Given that the length and width of a rectangle are multiplied to determine its area, we can state that any pair of non-negative integers whose product is equal to 60 would be appropriate.

Area = length × Width

We can find those integer numbers for its dimensions:

(60 divisors)

width × length

60 × 1

30 × 2

20 × 3

15 × 4

12 × 5

10 × 6

length × width

60 × 1

30 × 2

20 × 3

15 × 4

12 × 5

10 × 6

And many other combinations for non integers like 40 × 1.5, 24 × 2.5 etc.

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!!!!!!!!!!!!!!!!???????????

\(y=35+25=\bf60\)

Answer:

60

Step-by-step explanation:

find x first

180 - 35 - 25 = 120

x = 120

so y = 180-120

total angles in a triangle is 180

straight line also 180

Answer:

\( x = - 1 + 2i, \: \: - 1 - 2i\)

Step-by-step explanation:

\( {x}^{2} + 2x + 5 = 0 \\ \\ {x}^{2} + 2x + 1 + 4 = 0 \\ \\ {x}^{2} + 2x + 1 = - 4 \\ \\ {(x + 1)}^{2} = - 4 \\ \\ (x + 1) = \pm \sqrt{ - 4} \\ \\ x + 1 = \pm 2i \\ \\ x = - 1\pm 2i \\ \\ x = - 1 + 2i, \: \: x = - 1 - 2i \\ \\ x = - 1 + 2i, \: \: - 1 - 2i\)

Answer:

You'll need 18.85 feet of ribbon.

Step-by-step explanation:

The circumference is \(\pi d\).

\(\pi * 6 = 18.85\)

Data collected at the same, or approximately the same point in time are  Cross- sectional data

In statistics and econometrics, cross-sectional data, or a cross section of a study population, is a type of data gathered by monitoring numerous subjects (such as individuals, firms, countries, or regions) at one point or throughout the course of time. It's also possible that the analysis disregards variations in time. Cross-sectional data analysis often entails contrasting the variations among pre-selected respondents.

For instance, if we wanted to determine the prevalence of obesity in a population, we could randomly select a sample of 1,000 people (also referred to as a cross section of that population), measure their height and weight, and then determine what proportion of that sample falls under the definition of obesity. With the use of this cross-sectional sample, we are able to get a current picture of that group. Be aware that based on a single cross-sectional sample, we cannot determine whether the prevalence of obesity is rising or falling; we can only describe the current proportion.

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Answer: 6.50-.65 > 1.95x

Step-by-step explanation:

Answer: 3 Ib

Explanation: 6.50 - 0.65 = 5.85 and 1.95 times 3 is 5.85 so she spends the rest of her money on 3 pounds of tomatoes.

Answer:

0.8 degrees per hour

Step-by-step explanation:

1 2/5 divided by 1 3/4

7/5 / 7/4

keep, change, flip the fraction

7/5 x 4/7

=4/5= 0.8

Answer: C. The interquartile range (IQR) for town A, 15°, is less than the IQR for town B, 20°

Step-by-step explanation:

Picture

The maximum likelihood estimator of a is the minimum of the n observations {xi}

The data is generated i.i.d. from a uniform distribution [a, 1], the probability density function (pdf) of each observation is given by:

f(x; a) = 1/(1-a), for a ≤ x ≤ 1

= 0, otherwise

The likelihood function for n observations {xi}ni=1 is the product of their individual pdfs:

L(a; x1, x2, ..., xn) = ∏(1/(1-a)) = (1/(1-a))ⁿ, for a ≤ xi ≤ 1 for all i

The maximum likelihood estimate of a, we need to find the value of a that maximizes the likelihood function.

We can do this by finding the derivative of the log-likelihood function and setting it to zero:

ln L(a; x1, x2, ..., xn) = n ln(1/(1-a))

d/d(a) ln L(a; x1, x2, ..., xn) = -n/(1-a)

Setting the derivative to zero, we get:

n/(a-1) = 0

The derivative is negative for a < 1 and positive for a > 1, the maximum likelihood estimate of a is the smallest observation in the sample:

\(\^a = \^xn\)

= min {x1, x2, ..., xn}

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The maximum likelihood (ML) estimator of parameter a in the uniform distribution is ˆa = ˆxn.

In this scenario, we have a random variable x that follows a uniform distribution on the interval [a, 1]. The goal is to estimate the unknown parameter a using a training set {xi}ni=1, where each xi is independently and identically distributed (i.i.d.) from the uniform distribution on the same interval [a, 1].

The ML estimator seeks to find the parameter value that maximizes the likelihood function, which measures the probability of obtaining the observed data. In this case, the likelihood function is based on the order statistics of the training set.

The order statistic ˆxn represents the minimum value among the observations in the training set. Since the minimum value occurs when x is closest to the lower bound a, it is reasonable to use ˆxn as the ML estimator for a.

Therefore, the ML estimator of parameter a is ˆa = ˆxn, which corresponds to the minimum value observed in the training set.

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False. Not every t-distribution is symmetric around 0.

The statement that every t-distribution is symmetric around 0 is false. While the standard t-distribution with infinite degrees of freedom, known as the standard normal distribution, is symmetric around 0, t-distributions with finite degrees of freedom are not necessarily symmetric.

The shape of a t-distribution is determined by its degrees of freedom. As the degrees of freedom increase, the t-distribution approaches the standard normal distribution and becomes more symmetric around 0.

However, for smaller degrees of freedom, the t-distribution tends to have a slightly different shape with heavier tails compared to the standard normal distribution.

The symmetry of a t-distribution depends on the number of degrees of freedom. For an even number of degrees of freedom, the t-distribution is symmetric around 0.

However, for an odd number of degrees of freedom, the t-distribution is not symmetric and has a slight skewness. This means that the distribution is shifted slightly towards one side, either left or right, depending on the sign of the degrees of freedom.

Therefore, it is incorrect to claim that every t-distribution is symmetric around 0. The symmetry of a t-distribution depends on the specific degrees of freedom associated with it.

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Answer:

A = a/2^2 + b/2^2          where b = 26 - a     (a/2 and b/2 sides of square)

A = a^2 / 4 + 1/4 (a^2 - 52 a + 676)

4 * A= 2 a^2 - 52 a + 676

4 dA / da =4 a - 52 = 0

Area will be minimized when   a = 13 and b = 13

Check:  

 n A

13 13 0 84.5

12 14 1 85

11 15 2 86.5

10 16 3 89

9 17 4 92.5

8 18 5 97

7 19 6 102.5

6 20 7 109

5 21 8 116.5

4 22 9 125

3 23 10 134.5

2 24 11 145

1 25 12 156.5

0 26 13 169

Answer:

b=80-8t

Step-by-step explanation:

"b" represents the charge remaining

"t" represents the number of hrs that have passed.

"80" is the reference we will be subtracting the hours from.

"8" is the percentage per hour we will be subtracting

therefore, the equation b=80-8t would solve for the remaining battery after "t" number of hours.