The correct answer is (d) 64%. The coefficient of correlation (r) squared represents the percentage of variation in the dependent variable that is explained by the variation in the independent variable.
In this case, r squared is 0.8 squared, which equals 0.64 or 64%. Therefore, 64% of the variation in the dependent variable can be explained by the variation in the independent variable.
if the coefficient of correlation is 0.8, the percentage of variation in the dependent variable explained by the variation in the independent variable can be found by calculating the coefficient of determination (R²). In this case, R^2 = (0.8)² = 0.64, which means that 64% of the variation in the dependent variable is explained by the variation in the independent variable. Therefore, the correct answer is:
d. 64%
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Identify the critical t. An independent random sample is selected from an approximately normal population with unknown standard deviation. Find the degrees of freedom and the critical t value (t*) for the given sample size and confidence level.(a) n = 6, CL = 90%df=_____ t*=_____(b) n = 21, CL = 98%df=_____ t*=_____(c) n = 29, CL = 95%df=_____ t*=_____(d) n = 12, CL = 99%df=_____ t*=_____
The degrees of freedom and the critical t value (t*) for the given sample size and confidence level of the following are:
(a) df= 5, t*= 1.943; (b) df= 20, t*= 2.845; (c) df= 28, t*= 2.045; (d) df= 11, t*= 3.106.
The critical t value (t*) can be found using the t-distribution table, which takes into account the sample size and confidence level. The degrees of freedom (df) can be calculated using the formula df = n - 1.
(a) n = 6, CL = 90%
df= 5 t*= 1.943
Using the t-distribution table with 5 degrees of freedom and a confidence level of 90%, we find the critical t value to be 1.943.
(b) n = 21, CL = 98%
df= 20 t*= 2.845
Using the t-distribution table with 20 degrees of freedom and a confidence level of 98%, we find the critical t value to be 2.845.
(c) n = 29, CL = 95%
df= 28 t*= 2.045
Using the t-distribution table with 28 degrees of freedom and a confidence level of 95%, we find the critical t value to be 2.045.
(d) n = 12, CL = 99%
df= 11 t*= 3.106
Using the t-distribution table with 11 degrees of freedom and a confidence level of 99%, we find the critical t value to be 3.106.
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451,501,388,428,510,480, 390 which data values are outliers
Answer: To determine if any of these data values are outliers, you would first need to calculate the median and interquartile range (IQR) of the data set. You can then use the following rule to identify potential outliers:
- Any data value that is less than Q1 - 1.5(IQR) or greater than Q3 + 1.5(IQR) is a potential outlier.
Assuming the data set is in order, the median is 451.5 and the first and third quartiles are 389 and 495, respectively. The IQR is therefore 495 - 389 = 106. Using the rule above, we can check each data value to see if it is a potential outlier:
- 451 is not a potential outlier.
- 501 is not a potential outlier.
- 388 is not a potential outlier.
- 428 is not a potential outlier.
- 510 is not a potential outlier.
- 480 is not a potential outlier.
- 390 is not a potential outlier.
Therefore, there are no outliers in this data set.
Step-by-step explanation:
a uniformly charged thin rod lies along the x axis from x = 0 to x = +[infinity].
In this scenario, we have a uniformly charged thin rod extending along the x-axis from the origin (x = 0) to positive infinity (x = +∞).
The term "uniformly charged" means that the charge is distributed evenly throughout the entire length of the rod.
To analyze this situation, we can consider the following steps: 1. Determine the linear charge density (λ) of the rod. Since the rod is uniformly charged, λ remains constant along its entire length. λ is usually given in units of charge per length (e.g., coulombs per meter).
2. To find the electric field at a particular point along or outside the rod, we can break the rod into infinitesimally small segments (dx) and consider the contribution of the electric field (dE) from each of these segments.
3. Calculate the electric field (dE) produced by each segment at the desired point using Coulomb's equations , considering the linear charge density (λ) and distance between the segment and the point.
4. Integrate the electric field contributions (dE) from all segments along the entire length of the rod (from x = 0 to x = +∞) to find the total electric field (E) at the point of interest.
By following these steps, you can analyze the electric field and related properties of a uniformly charged thin rod extending along the x-axis from x = 0 to x = +∞.
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Formulate but do not solve the following exercise as a linear programming problem.
National Business Machines manufactures two models of portable printers: A and B. Each model A costs $120 to make, and each model B costs $140. The profits are $25 for each model A and $40 for each model B portable printer. If the total number of portable printers demanded per month does not exceed 3000 and the company has earmarked not more than $600,000/month for manufacturing costs, how many units of each model should National make each month to maximize its monthly profits P in dollars?
To formulate this problem as a linear programming problem, we need to identify the decision variables, objective functions, and constraints.
Decision Variables:
Let x be the number of model A printers manufactured per month, and y be the number of model B printers manufactured per month.
Objective Function:
The objective is to maximize monthly profits, which can be expressed as P = 25x + 40y.
Constraints:
1. The total number of printers demanded per month cannot exceed 3000, so we have the constraint x + y ≤ 3000.
2. The company has earmarked not more than $600,000/month for manufacturing costs, so the cost constraint is 120x + 140y ≤ 600,000.
3. The number of printers manufactured must be non-negative, so x ≥ 0 and y ≥ 0.
Therefore, the linear programming problem is:
Maximize P = 25x + 40y
Subject to:
x + y ≤ 3000
120x + 140y ≤ 600,000
x ≥ 0, y ≥ 0
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Given the circle below with secants � � � ‾ TUV and � � � ‾ XWV . If � � = 25 , � � = 22 UV=25,WV=22 and � � TU is 9 9 less than � � XW, find the length of � � ‾ TU . Round to the nearest tenth if necessary.
The specified secants, [tex]\overline{TUV}[/tex] and [tex]\overline{XWV}[/tex], evaluated using the intersecting secant theorem indicates that the length of the segment TU is 21 units
What is the intersecting secant theorem?The intersecting secant theorem states where two secants have the same endpoint external to or outside a circle, then the product of a secant and its external segment is equivalent to the product of the other secant and its external segment.
The specified segment lengths are;
UV = 25
WV = 22
TU = XW - 9
The intersecting secant theorem indicates that in the circle, we get;
[tex]\overline{TUV}[/tex]× UV = [tex]\overline{XWV}[/tex] × WV
[tex]\overline{TUV}[/tex] = TU + UV
[tex]\overline{XWV}[/tex] = XW + WV
UV = 25, WV = 22
TU = XW - 9
Therefore;
[tex]\overline{TUV}[/tex] = XW - 9 + 25 = XW + 16
[tex]\overline{XWV}[/tex] = XW + WV = XW + 22
Let x represent XW, we get;
[tex]\overline{TUV}[/tex]× UV = [tex]\overline{XWV}[/tex] + WV
(x + 16) × 25 = (x + 22) × 22
25·x + 400 = 22·x + 484
25·x - 22·x = 484 - 400 = 84
3·x = 84
x = 84/3 = 28
XW = 28, therefore;
TU = 28 - 9 = 21
TU = 21
Please find attached the possible diagram from the question, created with MS Word.
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In triangle ABC,a=6.5cm,b=8.5cm andc=4.5cm. Calculate: the largest angle the smallest angle the third angle
The largest angle is B and the smallest angle is C
What is the cosine rule?When we use the cosine rule, we can see that;
c^2 = a^2 + b^2 - 2ab Cos C
4.5^2 = 6.5^2 + 8.5^2 - 2(6.5 * 8.5) CosC
20.25 = 114.5 - 110.5CosC
20.25 - 114.5 = - 110.5CosC
CosC = 0.8529
C =Cos-1 0.8529
C = 31 degrees
Then;
b^2 = a^2 + c^2 - 2acCosB
8.5^2 = 6.5^2 + 4.5^2 -2(6.5 * 4.5)CosB
72.25 = 62.5 - 58.5CosB
72.5 - 62.5 = - 58.5CosB
Cos B = -0.1709
B = 100 degrees
Then;
A = 180 - (100 + 31)
A = 49 degrees
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Losses due to burglary are exponentially distributed with mean 100. The probability that a loss is between 40 and 50 equals the probability that a loss is between 60 and r, with r 60. Calculate r.
Answer: Let X be the random variable denoting the loss due to burglary. Then, we know that X is exponentially distributed with mean 100, which implies that the probability density function of X is given by:
f(x) = (1/100) * exp(-x/100) for x ≥ 0
The probability that a loss is between 40 and 50 can be expressed as:
P(40 ≤ X ≤ 50) = ∫40^50 f(x) dx
= ∫40^50 (1/100) * exp(-x/100) dx
= [-exp(-x/100)]40^50
= exp(-2/5) - exp(-1/2)
Similarly, the probability that a loss is between 60 and r can be expressed as:
P(60 ≤ X ≤ r) = ∫60^r f(x) dx
= ∫60^r (1/100) * exp(-x/100) dx
= [-exp(-x/100)]60^r
= exp(-3/5) - exp(-r/100)
Given that the above two probabilities are equal, we have:
exp(-2/5) - exp(-1/2) = exp(-3/5) - exp(-r/100)
Solving for r, we get:
r = -100 * ln [exp(-2/5) - exp(-1/2) + exp(-3/5)]
r ≈ 85.863
Therefore, the value of r is approximately 85.863.
Using a numerical solver, we can find the value of r: r ≈104.59. So, the value of r is approximately 67.35. To solve this problem, we can use the fact that the exponential distribution is memoryless, which means that the probability of a loss being between two values is the same no matter how much time has elapsed since the last loss.
Let X be the amount of the loss due to burglary. We know that X is exponentially distributed with mean 100, which implies that its probability density function (pdf) is given by f(x) = (1/100) * e^(-x/100) for x > 0.
The probability that a loss is between 40 and 50 is given by the integral of f(x) over that interval:
P(40 < X < 50) = integral from 40 to 50 of f(x) dx
= integral from 40 to 50 of (1/100) * e^(-x/100) dx
= e^(-40/100) - e^(-50/100)
= 0.3679 - 0.3679 * e^(-1/10)
= 0.0511 (rounded to four decimal places)
Now, let's find r such that the probability that a loss is between 60 and r is also 0.0511. We can set up the following equation:
P(60 < X < r) = integral from 60 to r of f(x) dx
= e^(-60/100) - e^(-r/100)
= 0.0511
Solving for r, we get:
e^(-r/100) = e^(-60/100) - 0.0511
r = -100 * ln(e^(-60/100) - 0.0511)
= 104.59 (rounded to two decimal places)
Therefore, r is approximately 104.59.
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Use the Chain Rule to find dz/ds and Oz/ot. (Enter your answer only in terms of s and t. Please use * for multiplication between all factors.) z = x2yº, x = s cos(t), y = s sin(t) ôz/05 = dz/dt =
The Chain Rule to find dz/ds and Oz/ot is
[tex]Oz/ot = dz/dt = -2s^2 cos(t) sin(t) = -2s^2 cos(t) * (y/x) = -2s^2 y sin(t) / x[/tex]
Thus, [tex]Oz/ot = -2s^2 y sin(t) / x.[/tex]
The chain rule is a rule in calculus that describes how to find the derivative of a composite function. If we have a function that is made up of two or more functions, the chain rule tells us how to find the derivative of the composite function.
To find dz/ds, we need to apply the Chain Rule, which states that if z is a function of u and u is a function of s, then:
dz/ds = dz/du * du/ds
In this case, we have:
[tex]z = x^2 * y^0 = x^2 = (s cos(t))^2 = s^2 cos^2(t)[/tex]
x = s cos(t)
y = s sin(t)
So, we can rewrite z as:
[tex]z = s^2 cos^2(t)[/tex]
Now, let's find du/ds and dz/du:
du/ds = d/ds (s cos(t)) = cos(t)
[tex]dz/du = d/ds (s^2 cos^2(t)) = 2s cos^2(t)[/tex]
Using the Chain Rule formula, we can now find dz/ds:
[tex]dz/ds = dz/du * du/ds = 2s cos^2(t) * cos(t) = 2s cos^3(t)[/tex]
Therefore,[tex]dz/ds = 2s cos^3(t).[/tex]
To find Oz/ot, we need to find dz/dt using the Chain Rule, and then substitute for z in terms of x and y:
dz/dt = dz/dx * dx/dt + dz/dy * dy/dt
[tex]dz/dx = 2xy^0 = 2x = 2s cos(t)[/tex]
[tex]dz/dy = x^2 * 0y^-1 = 0[/tex]
dx/dt = -s sin(t)
dy/dt = s cos(t)
Substituting these values in the Chain Rule formula, we get:
dz/dt = 2s cos(t) * (-s sin(t)) + 0 * (s cos(t)) = -2s^2 cos(t) sin(t)
Now, we can substitute for z in terms of x and y:
[tex]z = x^2 * y^0 = x^2 = (s cos(t))^2 = s^2 cos^2(t)[/tex]
Therefore, we have:
[tex]Oz/ot = dz/dt = -2s^2 cos(t) sin(t) = -2s^2 cos(t) * (y/x) = -2s^2 y sin(t) / x[/tex]
Thus, Oz/ot = -2s^2 y sin(t) / x.
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If in a population of 100 individuals, the allele frequency of the dominant allele is 0.8, how many homozygous dominant individuals are there? a. 64 b. 32 c. 16 d. 80
The answer is 64. To find the number of homozygous dominant individuals in the population.
We need to use the Hardy-Weinberg equation:
p^2 + 2pq + q^2 = 1
Where:
p = frequency of dominant allele
q = frequency of recessive allele
Since the dominant allele frequency is 0.8, we can assume that the recessive allele frequency is 0.2 (since p + q = 1).
To find the frequency of homozygous dominant individuals (p^2), we simply square the frequency of the dominant allele:
p^2 = (0.8)^2 = 0.64
To find the number of homozygous dominant individuals, we multiply the frequency by the total population size:
0.64 x 100 = 64
Therefore, there are 64 homozygous dominant individuals in the population.
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PLEASE HELP! I don’t understand this!
A system of linear equations that can be used to determine the number of DVDs Norma purchased and the number of DVDs Lauretta purchased is:
H. n + l = 14
n = 5/2(l)
How to determine the number of DVDs Norma and Lauretta purchased?In order to write a system of linear equations to describe this situation, we would assign variables to the number of DVDs Norma purchased and the number of DVDs Lauretta purchased, and then translate the word problem into an algebraic equation (linear equations) as follows:
Let the variable n represent the number of DVDs Norma purchased.Let the variable l represent the number of DVDs Lauretta purchased.Since Norma purchased two and a half times as many DVDs as Lauretta purchased, a linear equation that models the situation is given by;
n = 2 1/2l
n = (5/2)l = 5l/2
Additionally, they purchased a total of 14 DVDs together;
n + l = 14
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(x-y+z) (x+y+z)
Expand and find equation
Answer:
x² + z² + 2xz - y²
Step-by-step explanation:
(x - y + z) (x + y + z)
Rearranging to make it an identity,
=> (x + z + y) (x + z - y)
=> ((x + z) + y) ((x-z) - y)
We know the identity,
(a + b)(a-b) = a² - b²
=> (x + z)² - y²
We know the identity,
(a + b)² = a² + b² + 2ab
Expanding,
=> x² + z² + 2xz - y²
The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. What is the probability that a randomly selected tire will have a life of at most 47,500 miles? Show your answer to four decimal places (for example, 0.3217).
The probability that a randomly selected tire will have a life of at most 47,500 miles is 0.9332, or 93.32%.
To find the probability that a randomly selected tire will have a life of at most 47,500 miles, we need to calculate the z-score and use a standard normal distribution table.
The formula for the z-score is:
z = (x - μ) / σ
where x is the value we want to find the probability for, μ is the mean, and σ is the standard deviation.
Plugging in the values given in the problem, we get:
z = (47,500 - 40,000) / 5,000
z = 1.5
Using a standard normal distribution table, we can find that the probability of a z-score being less than or equal to 1.5 is 0.9332.
Therefore, the probability that a randomly selected tire will have a life of at most 47,500 miles is 0.9332 (or 93.32%) to four decimal places.
To answer your question, we will use the normal distribution, mean, standard deviation, and Z-score. Given that the life expectancy of the tire is normally distributed with a mean of 40,000 miles and a standard deviation of 5,000 miles, we will find the probability of a tire having a life of at most 47,500 miles.
First, we calculate the Z-score using the formula: Z = (X - μ) / σ, where X is the value we're interested in (47,500 miles), μ is the mean (40,000 miles), and σ is the standard deviation (5,000 miles).
Z = (47,500 - 40,000) / 5,000 = 7,500 / 5,000 = 1.5
Now, we look up the Z-score of 1.5 in a standard normal distribution table or use a calculator with a cumulative distribution function (CDF). The CDF value for a Z-score of 1.5 is approximately 0.9332.
So, the probability that a randomly selected tire will have a life of at most 47,500 miles is 0.9332, or 93.32%.
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Charlotte found a receipt for a pair of sneakers for $148.61, tax included. If the sales tax rate was 7 %, what was the list price of the sneakers?
Round your answer to the nearest cent.
$138.98 was the list price of the sneakers.
Let's use "x" to represent the trainers' list price. Given that the sales tax rate was 7%,
the tax amount corresponded to 0.07x, or 7% of the list price.
The total cost including tax was $148.61, so we can set up the following equation:
x + 0.07x = 148.61
Simplifying and solving for x, we get:
1.07x = 148.61
x = 138.98
Therefore, the list price of the sneakers was $138.98.
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A grocer selects five apples randomly from a box, weighs them and calculates an average weight of 165 grams. Match the feature of this process to the correct term.experiment -> selecting and weighing the apples (the experiment is the activity undertaken)outcome -> 165 grams average weight (a specific result of the experiment)event -> an average weight between 150 and 165 grams (an event is combination of one or more outcomes)random variable -> the average weight of five apples (a numerical rep of an outcome)
The grocer's selection and weighing of the apples is the experiment, while the specific result of the experiment - an average weight of 165 grams - is the outcome.
An event is a combination of one or more outcomes, such as an average weight between 150 and 165 grams. Finally, the average weight of five apples is the numerical representation of an outcome, which is known as the random variable.
Hi! I'd be happy to help explain these terms in the context of your question:
1. Experiment: Selecting and weighing the apples. This is the activity undertaken to gather data.
2. Outcome: The 165 grams average weight. This is a specific result of the experiment.
3. Event: An average weight between 150 and 165 grams. An event is a combination of one or more outcomes.
4. Random variable: The average weight of five apples. This is a numerical representation of an outcome.
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$690 is invested in an account earning 2.1% interest (APR), compounded continuously. Write a function showing the value of the account after t years, where the annual growth rate can be found from a constant in the function. Round all coefficients in the function to four decimal places. Also, determine the percentage of growth per year (APY), to the nearest hundredth of a percent.
A function showing the value of the account after t years is [tex]f(t) = 690(1.021)^{t}[/tex]
The percentage of growth per year (APY) is 21.22%.
How to write a function showing the value of the account after t years?In Mathematics and Financial accounting, continuous compounding interest can be determined or calculated by using this mathematical equation (formula):
[tex]f(t) = P_{0}e^{rt}[/tex]
Where:
f(t) represents the future value.P₀ represents the principal.r represents the interest rate.t represents the time measured in years.Based on the information provided above, we can reasonably infer and logically deduce that the function for the future value after t years is given by;
[tex]f(t) = 690(1 + 0.021)^{t}\\\\f(t) = 690(1.021)^{t}[/tex]
Growth per year (APY) = [tex]e^{r} =e^{0.021}[/tex]
Growth per year (APY) = 1.02122 - 1 = 0.2122 = 21.22%
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An ordinary deck of cards contains 52 cards divided into four suits. The red suits are diamonds (Ⓡ) and hearts (), and the black suits are clubs (%) and spades (~). Each suit contains 13 cards of the following denominations: 2, 3, 4, 5, 6, 7, 8, 9, 10, J (jack), Q (queen), K (king), and A (ace). The cards J, Q, and K are called face cards. Imagine choosing a card at random from a thoroughly mixed deck. Consider the event that the chosen card is red and has an even number on it. Which of the following expresses this event as a set? {2, 4, 6, 8, 100, 2, 4, 6, 8, 10•} {2, 40, 60, 80, 2, 4, 6, 8•} {24, 4a, 6A, 8A, 10A, 24, 44, 64, 84, 104} 24, 44, 6A, 8A, 104, 2, 4, 6, 8, 10v} {24, 44, 6A, 8A, 104, 24, 44, 64, 84, 104, 2, 4, 6, 8, 100, 2, 4, 6, 8, 10} What is the probability of this event?
The probability of this event is 3/13. The event described is choosing a red card with an even number from a deck. To express this event as a set, we will include all even-numbered cards from the red suits (diamonds and hearts). This set is: {2♦, 4♦, 6♦, 8♦, 10♦, 2♥, 4♥, 6♥, 8♥, 10♥}.
Now let's find the probability of this event. There are 52 cards in the deck and 10 cards in the event set. Therefore, the probability is:
P(event) = (number of favorable outcomes) / (total number of outcomes) = 10 / 52 = 5 / 26 ≈ 0.1923
The probability of choosing a red card with an even number from a deck is approximately 0.1923 or 19.23%.
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1) You test a new drug to reduce blood pressure. A group of 15 patients with high blood pressure report the following systolic pressures (measured in mm Hg): S 27.409 9 before medication: 181 114 145 137 154 162 175 191 127 122 124 189 124 141 187 151.53 after medication: 180 113 142 140 152 161 172 190 128 120 126 187 123 139 184 150.47 change: 1 1 3 -3 2 1 3 1 1 2 -2 2 1 2 3 1.067 26.691 1.7915 a) Calculate a 90% CI for the change in blood pressure. b) Calculate a 99.9% CI for the change in blood pressure. c) Does either interval (the one you calculated in (a) or (b)) include 0? Why is this important? d) Now conduct a one sample t-test using p= 0, and a = 10. Are the results consistent with (a)? Why or why not?e) Finally, conduct a one sample t-test using y = 0, and a =.001. Are the results consistent with (b)? Why or why not? /(Make sure you answer the part in bold for (d) and (e). See also problem 5) a
The 90% CI for the change in blood pressure is (-5.843, 7.977)., the 99.9% CI for the change in blood pressure is (-14.077, 16.211).
a) To calculate a 90% confidence interval (CI) for the change in blood pressure, we use the formula:
CI = x ± t(α/2, df) * (s/√n)
where x is the sample mean of the change in blood pressure, t(α/2, df) is the t-value for the desired confidence level and degrees of freedom, s is the sample standard deviation of the change in blood pressure, and n is the sample size.
Using the given data, we have:
x = 1.067
s = 26.691
n = 15
df = n - 1 = 14
From the t-distribution table, the t-value for a 90% confidence level and 14 degrees of freedom is 1.761.
Plugging in the values, we get:
CI = 1.067 ± 1.761 * (26.691/√15) = (-5.843, 7.977)
Therefore, the 90% CI for the change in blood pressure is (-5.843, 7.977).
b) To calculate a 99.9% CI for the change in blood pressure, we use the same formula but with a different t-value:
t(α/2, df) = 3.922 for a 99.9% confidence level and 14 degrees of freedom.
Plugging in the values, we get:
CI = 1.067 ± 3.922 * (26.691/√15) = (-14.077, 16.211)
Therefore, the 99.9% CI for the change in blood pressure is (-14.077, 16.211).
c) The interval calculated in part (a) does include 0, while the interval calculated in part (b) does not include 0. This is important because if the interval includes 0, it means we cannot conclude that there is a significant difference in blood pressure before and after the medication. On the other hand, if the interval does not include 0, it means we can be confident that there is a significant difference.
d) To conduct a one sample t-test with p = 0 and a = 10, we first calculate the t-statistic using the formula:
t = (x - p) / (s/√n)
where x is the sample mean of the change in blood pressure, s is the sample standard deviation of the change in blood pressure, and n is the sample size.
Plugging in the values, we get:
t = (1.067 - 0) / (26.691/√15) = 0.444
From the t-distribution table, the t-value for a one-tailed test with 14 degrees of freedom and a significance level of 10% is 1.345.
Since our calculated t-value (0.444) is less than the critical t-value (1.345), we fail to reject the null hypothesis that there is no significant difference in blood pressure before and after the medication. Therefore, the results are not consistent with the 90% CI calculated in part (a).
e) To conduct a one sample t-test with y = 0 and a = 0.001, we use the same formula as in part (d):
t = (x - y) / (s/√n)
Plugging in the values, we get:
t = (1.067 - 0) / (26.691/√15) = 0.444
From the t-distribution table, the t-value for a one-tailed test with 14 degrees of freedom and a significance level of 0.001 is 3.746.
Since our calculated t-value (0.444) is less than the critical t-value (3.746), we fail to reject the null hypothesis that there is no significant difference in blood pressure before and after the medication. Therefore, the results are not consistent with the 99.9% CI calculated in part (b).
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#7Change from standard form to vertex formy= x²-6x+7
So the vector form of the quadratic function y = x² - 6x + 7 is: y = (x - 3)² - 2.
To change from standard form to vertex form, we need to complete the square.
First, we group the x-terms together and factor out any common coefficient of x², giving:
y = x² - 6x + 7
y = 1(x² - 6x) + 7
Next, we need to add and subtract a constant inside the parentheses to complete the square. To determine this constant, we take half of the coefficient of x (-6) and square it:
(-6/2)² = 9
So we add and subtract 9 inside the parentheses:
y = 1(x² - 6x + 9 - 9) + 7
Now we can factor the quadratic expression inside the parentheses as a perfect square:
y = 1[(x - 3)² - 9] + 7
Simplifying and rearranging terms, we get:
y = (x - 3)² - 2
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Write the equation for each translation of the graph of y = 1 2 x − 2 + 3. one unit up
The equation for translation of the graph given is y = |x/2-2| + 4
Given is a function y = |x/2-2| + 3, it is translated one unit up, we need to find the translated function.
We know that, f(x) + k moves f(x) by k units up.
So, y = |x/2-2| + 3 → y = |x/2-2| + 3 + 1
y = |x/2-2| + 4
Hence, the equation for translation of the graph given is y = |x/2-2| + 4
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An airport limousine can accommodate up to four passengers on any one trip. The company will accept a maximum of six reservations for a trip, and a passenger must have a reservation. From previous records, 45% of all those making reservations do not appear for the trip. Answer the following questions, assuming independence wherever appropriate. (Round your answers to three decimal places.)
If six reservations are made, what is the probability that at least one individual with a reservation cannot be accommodated on the trip?
(a) The probability that at least one individual with a reservation cannot be accommodated on the trip is 0.4202.
(b) The expected number of available places when the limousine departs is 0.338.
How to solveLet the random variable Y represent the number of passenger reserving the trip shows up.
The probability of the random variable Y is, p = 0.70.
Success in this case an be defined as the number of passengers who show up for the trip.
The random variable Y follows a Binomial distribution with probability of success as 0.70.
(a)
It is provided that n = 6 reservations are made.
Compute the probability that at least one individual with a reservation cannot be accommodated on the trip as follows:
P (At least one individual cannot be accommodated) = P (X = 5) + P (X = 6)
= 0.4202
Thus, the probability that at least one individual with a reservation cannot be accommodated on the trip is 0.4202.
The expected number of available places when the limousine departs is 0.338.
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This diagram below shows a right
circular cone.
30 in.
A. 10 in.
B.
16 in.
C. 20 in.
D.
40 in.
36 in.
To the nearest inch, which of the
following is the diameter of the base of
the cone?
The diameter of the cone is 40 in. Option D
How to determine the diameterWe can see from the diagram shown, that the shape inside the cone is a triangle.
Thus, using the Pythagorean theorem which states that the square of the longest side which is the hypotenuse is equal to the sum of the squares of the other two sides.
We then have that;
36² = 30² + r²
find the squares
1296 = 900+ r²
collect like terms
r² = 396
Find the square root of the sides
r = 19. 89 in
Then,
Diameter = 2(radius)
Substitute
Diameter = 39. 79in
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A supervisor is setting up a display of cereal boxes. The ratio of frosted to unfrosted cereals in the display is 5: 7. Approximately what percent
of the cereal boxes are unfrosted?
A) 40.0%
B) 41.7%
C) 58.3%
https://www.an engineer has designed a valve that will regulate water pressure on an automobile engine. the valve was tested on 160 engines and the mean pressure was 6.2 lbs/square inch. assume the standard deviation is known to be 0.9 . if the valve was designed to produce a mean pressure of 6 lbs/square inch, is there sufficient evidence at the 0.05 level that the valve performs above the specifications?/homework-help/questions-and-answers/1-engineer-designed-valve-regulate-water-pressure-automobile-engine-valve-tested-120-engin-q107788593?trackid
t = (sample mean - hypothesized mean) / (standard deviation / square root of sample size)
Substituting the values given in the question, we get:
t = (6.2 - 6) / (0.9 / sqrt(160))
t = 5.46
Since the p-value is less than the significance level of 0.05, we can reject the null hypothesis and conclude that there is sufficient evidence at the 0.05 level that the valve performs above the specifications.
To determine if there is sufficient evidence at the 0.05 level that the valve performs above the specifications, we will perform a hypothesis test using the given information.
Step 1: State the null and alternative hypotheses.
Null hypothesis (H0): The mean water pressure is equal to 6 lbs/square inch (µ = 6).
Alternative hypothesis (H1): The mean water pressure is greater than 6 lbs/square inch (µ > 6).
The null hypothesis (H0) is that the mean pressure produced by the valve is 6 lbs/square inch, and the alternative hypothesis (Ha) is that the mean pressure produced by the valve is greater than 6 lbs/square inch.
We can use a one-sample t-test to test this hypothesis.
The test statistic is calculated as:
t = (sample mean - hypothesized mean) / (standard deviation / square root of sample size)
Step 2: Calculate the test statistic.
The test statistic (z) = (sample mean - population mean) / (standard deviation/sqrt (sample size))
z = (6.2 - 6) / (0.9 / sqrt(160))
z ≈ 3.11
Step 3: Determine the critical value and make a decision.
Using a t-distribution table with 159 degrees of freedom (160-1), we find that the probability of getting a t-value of 5.46 or greater is very small, less than 0.0001.
Since this is a one-tailed test at the 0.05 significance level, we will compare the test statistic (z) to the critical value from the z-table. The critical value for a one-tailed test at a 0.05 significance level is 1.645.
Since the test statistic (3.11) is greater than the critical value (1.645), we reject the null hypothesis in favor of the alternative hypothesis.
Conclusion: There is sufficient evidence at the 0.05 level that the valve performs above the specifications, as the mean water pressure is greater than 6 lbs/square inch.
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38. Make a stem and left plot of following data of Video game scores:
{542, 529, 564, 531, 456, 540, 522, 548, 531}
Answer:
Below
Step-by-step explanation:
There is an image uploaded below of the stem-and-leaf plot of the video game scores!
Last week, a dairy farm produced pkg of cheese.
The dairy farm also produced 24 kg more yoghurt than cheese and 3 times as much ice cream as cheese.
The dairy farm produced more kilograms of ice cream than yoghurt last week.
Write and solve an inequality to work out the possible values of p.
The inequality that represents the given condition is "p > 12".
Let p be the amount of cheese produced in kg.
Then, the amount of yogurt produced is (p + 24) kg (since it is 24 kg more than cheese). And the amount of ice cream produced is 3p kg (since it is 3 times as much as cheese).
Now, we need to find the possible values of p that satisfy the condition "the dairy farm produced more kilograms of ice cream than yogurt last week." In other words, we need to compare the amount of ice cream produced (3p) with the amount of yogurt produced (p + 24) and ensure that the amount of ice cream is greater.
So, we can write the following inequality:
3p > p + 24
Simplifying this inequality, we get:
2p > 24
Dividing both sides by 2, we get:
p > 12
Therefore, the possible values of p that satisfy the given condition are all values of p greater than 12.
In summary, the inequality that represents the given condition is "p > 12".
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Your job is to randomly select integrated circuits, and then test them in sequence until you find the first failure. let be the total number of tests, and assume that all tests are independent with probability of failure. Identify the type of random variable and its parameter(s).
The type of random variable in this scenario is a geometric random variable. Its parameter is the probability of failure for each integrated circuit being tested.
The type of random variable you're dealing with in this scenario, where you are testing integrated circuits in sequence until you find the first failure, is called a Geometric Random Variable. This type of random variable represents the number of trials needed for the first success (or failure, in this case) in a series of independent Bernoulli trials with the same probability of failure. The parameter for a Geometric Random Variable is the probability of failure, denoted as p. In summary, the type of random variable in this problem is a Geometric Random Variable, and its parameter is the probability of failure (p).
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A party planner organized a dinner party. The party planner recorded the height of the candlesticks over time and graphed the relationship. graph with the x axis labeled time in hours and the y axis labeled height of candlestick in inches and a line going from the point 0 comma 9 through the point 3 comma 7 Find and interpret the slope and y-intercept in this real-world situation. The slope is negative two thirds, and the y-intercept is 9. The candle starts at a height of 9 inches and decreases two thirds of an inch every hour. The slope is negative three halves, and the y-intercept is 9. The candle starts at a height of 9 inches and decreases three halves of an inch every hour. The slope is 9, and the y-intercept is negative two thirds. The candle starts at a height of two thirds of an inch and decreases 9 inches every hour. The slope is 9, and the y-intercept is negative three halves. The candle starts at a height of three halves of an inch and decreases 9 inches every hour.
The slope and the y intercepts of the given graph which shows height of the candlesticks over time is :
Slope = -2/3
Y intercept = 9
The graph is that of the height of the candlesticks over time.
The line passes through two points (0, 9) and (3, 7).
Slope of the line can be calculated as,
Slope = (7 - 9) / (3 - 0) = -2/3
Hence the slope id negative two thirds.
y intercept of a graph is the y coordinate of the point where the line touches the Y axis.
The x coordinate will be 0 there.
The line passes through (0, 9).
So y intercept = 9
Hence the slope and the y intercept are -2/3 and 9 respectively.
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The length of a model car is 1/20 of the length of the actual car. If the model is 9.3 inches long write an equation where c represents the actual length of the car
Geometry statements please.
It is concluded that TU ≅ UV is by the definition of congruence as shown in the solution part.
As per the given figure, the required proof would be as:
Statements:
1. U is the midpoint of SW.
2. T is the midpoint of SU.
3. V is the midpoint of UW.
4. TU || WV (by midpoint theorem)
5. TV || UW (by midpoint theorem)
6. UT = TV (by midpoint theorem)
7. UV = 2VT (by midpoint theorem)
Reasons:
1. Given.
2. Given.
3. Given.
4. Midpoint theorem.
5. Midpoint theorem.
6. Midpoint theorem.
7. Midpoint theorem.
Therefore, TU ≅ UV by the definition of congruence.
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the cdc recommends that adults eat a certain number of servings of fruits and vegetables per day. what proportion of adults meet the guidelines for fruit and vegetable consumption that are set by the cdc? in a survey of a random sample of 1000 adults, 14% reported eating the number of daily servings of fruits and vegetables that are recommended by the cdc. if we want to use this information to construct a 90% confidence interval, what will the margin of error be? a. 0.032 b. 0.003 c. 0.018 d. 0.051 e. 0.022
Based on the information given, we know that 14% of the sample of 1000 adults reported meeting the daily serving recommendations for fruits and vegetables set by the CDC. To construct a 90% confidence interval, we need to calculate the margin of error.
We can use the formula:
[tex]Margin of error = z* (sqrt(p*(1-p)/n))[/tex]
Where:
z* is the critical value for a 90% confidence interval, which is 1.645
p is the proportion of the sample that met the CDC recommendations, which is 0.14
n is the sample size, which is 1000
Plugging in the values, we get:
Margin of error = 1.645 * (sqrt(0.14*(1-0.14)/1000))
Margin of error ≈ 0.022
Therefore, the answer is e. 0.022.
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