Each side of a square is increased 3 inches. When this happens, the area is multiplied by 25. How many inches in the side of the original square?

Answer:

standard

Step-by-step explanation:

The sum of the Arithmetic Progression 5 + 8 + 11 + ... + 122 is 2540.

Here we are given to find the sum of 5 + 8 + 11 + ... + 122

Here we can see that this is an Arithmetic Progression with the first term as 5 and the common difference as

second term - first term

= 8 - 5

= 3

Here we need to find the sum from 5 to 122

now, we know that for any term

aₙ = a + (n - 1)d

where,

a = first term

d = common difference

hence putting aₙ as 122 we get

5 + (n - 1)3 = 122

or, 5 + 3n - 3 = 122

or, 3n + 2 = 122

or, 3n = 120

or, n = 40

Hence, we need to find the sum of the first n terms

we know that the sum S is

S = 0.5n(a + aₙ)

here we know that n = 122, a = 5 and aₙ = 122

hence we get

S = 0.5 X 40(5 + 122)

= 20(127)

= 2540

Hence the sum is 2540.

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Answer:

y intercept is (0, 2/3)

Step-by-step explanation:

the y-inetercept is 0

i don’t know the exponential

growth or exponential decay but you can use math.way to help you answer the question

Answer:

77 degrees

Step-by-step explanation:

All triangle add up to 180 degrees and right triangle all have one angle that is 90 degrees so 90 + 14 is 104 and 180 - 104 is 77.

Answer:

76 degrees

Step-by-step explanation:

What we know:

1. the triangle is a right triangle, meaning on angle has to be 90 degrees

2. One angle is 14 degrees

3. A triangle's angles add up to 180 degrees.

----------------------------------------------------------------------------------------------------

90+14+x=180

104+x=180

x=76

The expected amount that you would win is approximately $0.334891, and the probability of losing $300,000 or more is approximately 0.00030986749 (or 0.030986749%).

To calculate the expected amount that you would win in this scenario, we need to consider the probabilities of various outcomes and their corresponding winnings.

(a) Expected Amount of Winnings:

Let's calculate the expected amount by considering the probabilities and winnings for different outcomes:

- Probability of matching exactly 5 out of 6 numbers:

The probability of matching 5 numbers correctly is given by the combination formula:

P(5) = C(6, 5) * C(40, 1) / C(46, 6) = 0.00000096739

The corresponding winnings are $100,000.

- Probability of matching exactly 4 out of 6 numbers:

The probability of matching 4 numbers correctly is given by the combination formula:

P(4) = C(6, 4) * C(40, 2) / C(46, 6) = 0.0000186101

The corresponding winnings are $5,000.

- Probability of matching exactly 3 out of 6 numbers:

The probability of matching 3 numbers correctly is given by the combination formula:

P(3) = C(6, 3) * C(40, 3) / C(46, 6) = 0.000290201

The corresponding winnings are $500.

Now, let's calculate the expected amount:

Expected Amount = (P(5) * $100,000) + (P(4) * $5,000) + (P(3) * $500)

Expected Amount = (0.00000096739 * $100,000) + (0.0000186101 * $5,000) + (0.000290201 * $500)

Expected Amount = $0.096739 + $0.093051 + $0.145101

Expected Amount = $0.334891

Therefore, the expected amount that you would win is approximately $0.334891.

(b) Probability of Losing $300,000 or More:

To derive a bound on the probability of losing $300,000 or more, we need to calculate the cumulative probability of having 3 or fewer of the 5 winning tickets.

Cumulative Probability = P(3) + P(4) + P(5)

Cumulative Probability = 0.000290201 + 0.0000186101 + 0.00000096739

Cumulative Probability = 0.00030986749

Therefore, the bound on the probability of losing $300,000 or more is approximately 0.00030986749, which is equivalent to 0.030986749%.

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Answer:

It converges

Step-by-step explanation:

dx/dy = x∧4 + 9x∧21

f(x) = ∫(x∧4 + 9x∧21)dy        0  > f(x) > ∞

= x∧5/5 + 9x∧22/22 + c  

    x = ∞ and x = 0

∴ c = 1 /5 +  9/22 = 27/22

Answer:

126 yds will be your answer.

Step-by-step explanation:

30+(24+24)+4+2+(3+3)+(4+30+2)=126

just add all of the sides up.

The probability that a randomly selected American plans to stay home or travel by car over the next holiday weekend given the information that 9.35% of Americans plan to travel by car and 88.6% plan to stay home. The probability of staying home or traveling by car over the next holiday weekend is given by the addition of probabilities of these events.

P(stay home or travel by car) = P(stay home) + P(travel by car)P(stay home or travel by car) = 0.886 + 0.0935P(stay home or travel by car) = 0.9795Therefore, the probability that a randomly selected American plans to stay home or travel by car over the next holiday weekend is 0.9795.

The value of probability does not equal 1 because some Americans traveled by other means.

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Answer: True

Explanation:

1 centimeter = 10 millimeters

Buster = 75 millimeters long

Bubbles = 60 millimeters long

Answer:

1 shirt costs $11.2 1 hat costs $10.

Step-by-step explanation:

35 divided by 3

20 divided by 2

Answer:

0.2857 is not a rational number.

Step-by-step explanation:

Because rational numbers have to be greater than 1. Decimals are not over 1 so it is not a rational number. Your welcome!

Answer:

a

Step-by-step explanation:

Answer:

9 servings

There should be an answer to that. Answer: There are 9 servings. step- by- step Explanation: We would first divide 22.5/2.5. This will give us the amount of time 2.5 will go into 22.5, providing us with the amount of servings

Step-by-step explanation:

Answer:

The population of Bear in 2050 is 4750000

Step-by-step explanation:

A) The exponential growth equation for bear is as follows -

dN/dT = rmax * N

Where dN/dT = change in population

rmax is the maximum rate of change

N = Base population

B) Here the per capita rate of increase (r) will always be a positive value irrespective of the and hence we will assume this population to be growing exponentially.

C) dN/dT = rmax * N

D) dN / 5 = 2.5 * 380,000

dN = 5*2.5 * 380000

= 4750000

Answer:

y = -1/3x + 4

Step-by-step explanation:

(-9, 7) and (3, 3)

Slope:

m=(y2-y1)/(x2-x1)

m=(3-7)/(3+9)

m=(-4)/12

m= -1/3

Slope-intercept:

y - y1 = m(x - x1)

y - 7 = -1/3(x + 9)

y - 7 = -1/3x - 3

y = -1/3x + 4

Step-by-step explanation:

[tex]soln \\ \frac{3 - 7 }{3 - - 9} \\ = \frac{ - 4}{ - 12} \\ = \frac{1}{3 } \\ \frac{y - 7}{x - 3} = \frac{1}{3} \\ then \: you \: cross \: multiplication. \\ 3(y - 7) = 1(x - 3) \\ 3y - 7 = x - 3 \\ 3y = x - 3 + 7 \\ 3y = x + 4 \\ \frac{3y}{3} = \frac{x}{3} + \frac{4}{3} \\ y = \frac{x}{3} + \frac{4}{3} [/tex]

Answer:

5/8

Step-by-step explanation:

I have the same problem and this answer was correct.

The table shows the number of games a team won and lost last season with a ratio of win to loss as 3:2. Therefore the tool most appropriate for use is a 5-section spinner with congruent sections, 3 representing a win and 2 representing a loss.

Ratio, in math, is a term that is used to compare two or more numbers. It is used to indicate how big or small a quantity is when compared to another. In a ratio, two quantities are compared using division.

here, we have,

To calculate a win-to-loss ratio, divide the number of wins by the number of losses.

According to the given data:

Greg is creating a simulation, using previous year’s wins and losses, to foretell the team's conclusion.

Wins in the last season = 24

losses in the last season = 16

Ratio of wins and losses = 24:16 = 3:2

Chances of the team winning out of 5 matches is 3 and losing is 2.

The device which is most suitable for application in a simulation that implements the data is a 5-section spinner with congruent sections, 3 representing a win and 2 representing a loss.

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complete question:

the table shaws the number of games a team won and lost last season. Wins and losses last season number of games wins 24 losses 16 greg has tickets to six of the team’s games this season. He is designing a simulation, using last year’s wins and losses, to predict whether the team will win or lose each of the games he attends. Which tool is most appropriate for use in a simulation that fits the data?

1 a coin with one side representing a win and the other representing a loss

2 a 6-section spinner with congruent sections, 4 representing a win and 2 representing a loss

3 a 5-section spinner with congruent sections, 3 representing a win and 2 4representing a loss an 8-sided die with 5 sides representing a win and 3 sides representing a loss

Answer:

200

Step-by-step explanation:

103+94

=100+100

=200

Answer:

197 the nearest ten is 200

Step-by-step explanation:

he need to put the nearest ten

GIS can assist in location decision-making by combining geography with demographic analysis, automating center-of-gravity problems, providing spatial data for transportation planning, enhancing factor-rating analysis with spatial considerations, and indirectly informing Internet placement for virtual storefronts.

Geographic Information Systems (GIS) can assist in location decision-making by combining geography with demographic analysis (D). GIS technology enables the integration and analysis of various spatial data, including demographic information such as population density, income levels, and consumer behavior.

By overlaying geographic data with demographic data, decision-makers can gain valuable insights into the characteristics and preferences of target markets, helping them identify suitable locations for their businesses.

GIS can automate center-of-gravity problems (C) by applying spatial analysis techniques to determine optimal locations based on factors such as customer demand, transportation networks, and supply chain considerations.

By utilizing GIS, businesses can identify central points or distribution hubs that minimize transportation costs and maximize accessibility to target markets.

While GIS doesn't directly update transportation method solutions (A), it can provide valuable spatial data and analysis that inform transportation planning. This includes mapping and visualizing existing transportation infrastructure, identifying traffic patterns, and optimizing routes for efficient logistics.

Although GIS doesn't computerize factor-rating analysis (B) per se, it can enhance this process by providing a spatial dimension. Factor-rating analysis involves evaluating potential locations based on multiple factors such as cost, labor availability, and market proximity. GIS can incorporate spatial data, such as the proximity of suppliers or competitors, into the factor-rating analysis, enabling more informed decision-making.

GIS may indirectly contribute to providing good Internet placement for virtual storefronts (E). By analyzing factors such as population density, internet infrastructure, and connectivity patterns, GIS can help businesses identify areas with a high potential for online customer engagement. However, the direct responsibility of Internet placement lies more within the realm of network infrastructure and internet service providers.

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The equation y = 150 - 0.01x^2 represents the height of the kite above the ground as a function of its horizontal position x. The kite travels a distance of 80 ft.

The equation y = 150 - 0.01x^2 represents the height of the kite above the ground as a function of its horizontal position x. This is a downward-opening parabola, with the vertex at (0, 150) and the axis of symmetry along the y-axis.

To find the distance traveled by the kite, we need to determine the range of x over which the kite is flying. In this case, the range is from x = 0 to x = 80 ft.

The distance traveled by the kite is the difference between the initial and final positions of x. In this case, it is 80 - 0 = 80 ft.

Therefore, the kite travels a distance of 80 ft.

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a) The probability of drawing 17 red balls and 8 blue balls from boxes with even-numbered labels is 0.0051.

b) The probability of drawing 17 red balls and 8 blue balls from boxes with even-numbered labels, given that the fifth ball drawn was red, is 0.1926.

a) The probability of drawing 17 red balls and 8 blue balls from boxes with even-numbered labels can be calculated as follows:

P(drawing 17 red balls and 8 blue balls from boxes with even-numbered labels) = (C(25, 17) × C(25, 8)) / C(50, 25)

= (12620256 / 2462624626080)

= 0.0051 (approx)

Therefore, the probability of drawing 17 red balls and 8 blue balls from boxes with even-numbered labels is 0.0051 (approx).

b) If accidentally, you see the fifth ball after being drawn is red, then the corresponding box will be removed, and there are now 49 boxes remaining on the table.

The number of even-numbered boxes among these 49 boxes is 24.

Therefore, the probability of drawing 17 red balls and 8 blue balls from boxes with even-numbered labels, given that the fifth ball drawn was red, can be calculated as follows:

P(drawing 17 red balls and 8 blue balls from boxes with even-numbered labels, given that the fifth ball drawn was red)

= (C(24, 16) × C(25, 7)) / C(49, 23)

= (8751600 / 45379690908)

= 0.1926 (approx)

Therefore, the probability of drawing 17 red balls and 8 blue balls from boxes with even-numbered labels, given that the fifth ball drawn was red, is 0.1926 (approx).

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Answer:

-2x+2

Step-by-step explanation:

it is directly underneath the original equation and they never intersect

Answer: Its A

Step-by-step explanation: Just count the lines and since there is 8 lines it would be ?/8 so we going to count up until the dot which stops at 3 soo it would be 3/8

The correct answer is:

D. 0.981.

To calculate the probability that the sample mean IQ is greater than 115, we need to use the concept of sampling distribution and the central limit theorem.

Given:

Population mean (μ) = 112

Population standard deviation (σ) = 25

Sample size (n) = 300

The mean of the sampling distribution of the sample means (μx) will be the same as the population mean (μ) which is 112.

The standard deviation of the sampling distribution (σx) can be calculated using the formula:

σx = σ / √(n)

Plugging in the values:

σx = 25 / √(300)

≈ 1.443

Now, we can use the z-score formula to standardize the sample mean:

z = (x - μx) / σx

where x is the sample mean.

Plugging in the values:

z = (115 - 112) / 1.443

≈ 2.08

Next, we need to find the probability that the standardized sample mean (z) is greater than 2.08.

This can be done by looking up the z-score in the standard normal distribution table or by using a calculator or statistical software.

Using a standard normal distribution table or calculator, we find that the probability associated with a z-score of 2.08 is approximately 0.981.

Therefore, the correct answer is:

D. 0.981.

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(a) Using these variables, the dimensionless variables that can be used for this problem are as follows:2d/gdgb/EiE/b

(b) If the density is the same, the model ice can have the same strength properties as that of the prototype ice.

(a) The suitable set of dimensionless variables for this problem includes: g, the acceleration of gravityd, depth of the iceb, pier width Ei, the strength of the ice ρ, density of the ice

Using these variables, the dimensionless variables that can be used for this problem are as follows:2d/gdgb/EiE/b

(b) Given that the length scale is 1/21, and prototype ice thickness and velocity are 12 in. and 11 ft/s, respectively.

We can determine the model ice thickness and velocity using the length scale as follows:

For ice thickness, Model ice thickness = Prototype ice thickness × Length scale= 12 in. × (1/21)= 0.571 in.

For ice velocity, Model ice velocity = Prototype ice velocity × (Length scale)-0.5= 11 ft/s × (1/21)-0.5= 0.765 ft/s≈ 0.77 ft/s(c)

The model ice can have the same strength properties as the prototype ice if their strengths are identical, although the densities are the same.

Therefore, if the density is the same, the model ice can have the same strength properties as that of the prototype ice.

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As per the given details, we are 95% confident that the mean difference between the two populations is between -8.86 and 9.86.

Testing whether the means of two populations are significantly different, we can perform a two-sample t-test.

Given that:

Sample data for Population 1: 19, 17, 3.9

Sample data for Population 2: 19, 13.8, 4.6

Using a significance level of α = 0.05, we can conduct the two-sample t-test.

Calculating the sample means:

X1 = (19 + 17 + 3.9) / 3 = 13.3

X2 = (19 + 13.8 + 4.6) / 3 = 12.8

Calculating standard deviations (s₁ and s₂):

s₁ = sqrt(((19 - 13.3)² + (17 - 13.3)² + (3.9 - 13.3)²) / 2) ≈ 8.16

s₂ = sqrt(((19 - 12.8)² + (13.8 - 12.8)² + (4.6 - 12.8)²) / 2) ≈ 5.44

Calculating the test statistic:

t = (X1 - X2) / sqrt((s₁² / n₁) + (s₂² / n₂))

 = (13.3 - 12.8) / sqrt((8.16² / 3) + (5.44² / 3))

 ≈ 0.489

Degrees of freedom (df) = n₁ + n₂ - 2 = 3 + 3 - 2 = 4

Since |t| = 0.489 < 2.776, we fail to reject the null hypothesis.

Constructing a 95% confidence interval for the mean difference, we can use the formula:

Confidence Interval = (X1 - X2) ± t * sqrt((s₁² / n₁) + (s₂² / n₂))

Using the given values and a confidence level of 95%:

X1 - X2 = 13.3 - 12.8 = 0.5

t (with df = 4, α/2 = 0.025) ≈ 2.776

The standard error:

SE = sqrt((s₁² / n₁) + (s₂² / n₂)) = sqrt((8.16² / 3) + (5.44² / 3)) ≈ 3.37

Confidence Interval = 0.5 ± 2.776 * 3.37

                  = 0.5 ± 9.36

                  ≈ (-8.86, 9.86)

Thus, we are 95% confident that the mean difference between the two populations is between -8.86 and 9.86.

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