Part A

An economist has measured people's annual salary (in thousands of dollars) and their years of relevant job experience, thinking that a linear relationship between them might exist.

Let the proposed regression relationship between Salary and experience be as follows: E(Salary) = beta subscript 0 space plus space beta subscript 1 space cross times Years of Experience

and assume the output from running the regression is as follows:

Call:

lm(formula = Salary ~ Year, data = Income)

Residuals:

Min 1Q Median 3Q Max

-53.650 -20.256 0.127 18.423 65.596

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 31.8387 8.5565 3.721 0.00033***

Years 2.8205 0.3302 8.543 1.74e-13 ***

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 25.98 on 98 degrees of freedom

Multiple R-squared: 0.4268, Adjusted R-squared: 0.421

F-statistic: 72.98 on 1 and 98 DF, p-value: 1.737e-13

---

Residual standard error: 8.044 on 445 degrees of freedom

Multiple R-squared: 0.6914, Adjusted R-squared: 0.6886

F-statistic: 249.2 on 4 and 445 DF, p-value: < 2.2e-16

If we wished to conduct a hypothesis test as to whether there is a linear relationship between salary and years of experience, what are the correct null and alternate hypotheses?

Answers:

a.

H subscript 0 : space beta subscript 0 space equals space 0 H subscript 1 : space beta subscript 0 greater than space 0

b.

H subscript 0 : space beta subscript 0 space equals space 0 H subscript 1 : space beta subscript 0 space end subscript not equal to space 0

c.

H subscript 0 space : thin space beta subscript 1 space equals space 0 H subscript 1 : space beta subscript 1 space end subscript space not equal to space 0

d.

H subscript 0 : space beta subscript 1 space equals space 0 H subscript 1 : space beta subscript 1 space greater than space 0

Part B

Using the output in Q1, what is the correct p-value for the test in Q1?

Answers:

a.

0.00033

b.

0.000000000000174

c.

1.74e-13

d.

0.00000393

Part C

What is the fitted regression model from this output in Q1?

Answers:

a.

E(Salary) = 31.8387 + 2.8205 x Years of Experience

b.

E( Years of Experience ) = 2.8205 + 31.8387 x Salary

c.

E( Years of Experience ) = 31.8387 + 2.8205 x Salary

d.

E(Salary) = 2.8205 + 31.8387 x Years of Experience

Part D

Which of the following is a correct statement regarding r squared ?

Answers:

a.

r squared space equals space 0.4268 meaning that Years of Experience explains 42.68 percent sign of the variability in Salary.

b.

r squared space equals space 0.00033 meaning that Years of Experience explains 0.033 percent sign of the variability in Salary.

c.

r squared space equals space 0.00033 and because 0.00033 space less than space 0.05 we reject H subscript 0 and accept H subscript 1 at the 5% level of significance, ie we conclude there is a significant linear relationship between Salary and Years of Experience.

d.

r squared space equals space 0.4268 and because 0.4268 space greater than space 0.05 we do not reject H subscript 0 at the 5% level of significance, ie we conclude there is no significant linear relationship between Salary and Years of Experience.

Answer:

1 shirt costs $11.2 1 hat costs $10.

Step-by-step explanation:

35 divided by 3

20 divided by 2

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:

a

Step-by-step explanation:

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

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

A. The volume of the solid formed by rotating the region bounded above by the parabola y = 3x-x² and y = 0 around the vertical line x = -1 is approximately 9.74 cubic units and B. The inverse function is found to be ln(x/(1 - x)).

To find the volume of the solid, we can use the method of cylindrical shells. The integral for the volume is given by V = ∫[a,b] 2πxf(x) dx, where f(x) represents the height of the shell at each x-coordinate.

First, we need to find the bounds of integration. The parabola y = 3x - x² intersects the x-axis at x = 0 and x = 3. Therefore, the bounds of integration are [0, 3].

Next, we need to express the height of the shell, f(x), in terms of x.

Evaluating the integral, we get V = ∫[0,3] 2π(x + 1)(3x - x²) dx. After integrating and simplifying, the volume is approximately 9.74 cubic units.

(B) To find the inverse of the function f(x), we swap the roles of x and y and solve for y. So, we start with y = eˣ/(1 - eˣ).

Step 1: Swap x and y: x = eʸ/(1 - eʸ).

Step 2: Solve for y: x(1 - eʸ) = eʸ.

Step 3: Expand and isolate eʸ: x - xeʸ = eʸ.

Step 4: Factor out eʸ: eʸ(x - 1) = x.

Step 5: Divide both sides by (x - 1): eʸ = x/(x - 1).

Step 6: Take the natural logarithm of both sides: y = ln(x/(x - 1)). Thus, the inverse function is g(x) = ln(x/(x - 1)), where x ∈ (0, 1).

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Complete question - A. The region bounded above by the parabola y = 3x-x2² and y = 0 is rotated around a vertical line x=-1 forming a solid, find its volume.

B. Given the following function which is one to one f(x) = eˣ/1-eˣ Find its inverse.

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:

-2x+2

Step-by-step explanation:

it is directly underneath the original equation and they never intersect

Answer: True

Explanation:

1 centimeter = 10 millimeters

Buster = 75 millimeters long

Bubbles = 60 millimeters long

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

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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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:

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:

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:

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 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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(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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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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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:

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

Answer:

standard

Step-by-step explanation:

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 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:

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!