If the warehouse is 10 feet tall what could the side lengths of the floor be

Answer:

Check the explanation

Step-by-step explanation:

Going by the question, the design is RBD (Randomized Block Design). Where the blocks are nothing but a Combination of Soil Types(I, II, III, IV and V).So here we have seen 5 blocks.Fertilizers can be considered as treatments(A,B and C).

Fertilizer A Fertilizer B Fertilizer C

Soil I    2                  2                 2

Soil II 2                 2                 2

Soil III 2                 2                 2

Soil III 2                 2                 2

Soil IV 2                 2                 2

Model for a randomized block design

The model for a randomized block design with one nuisance variable is

[tex]Y_{ij}=\mu +T_{i}+B_{j}+\mathrm {random\ error}[/tex]

where

is any observation

μ is the general location parameter (i.e., the mean)

is the effect for being in treatment i (Fertilizer)

[tex]B_j[/tex] is the effect for being in block j (Type of Soil)

Answer:

a. We fail reject to the null hypothesis because zo = -5.84 < 1.65 = zα and P-value = 1 (approximately)

b. The confidence Interval for u1 - u2 is; 6.79 ≤ u1 - u2

c. The power of the test = 1 -

β = 0.998736

d. The sample size is adequate because the power of the test is approximately 1

Step-by-step explanation:

Given

Standard Deviations; σ1 = σ2 = 1.0 psi

Size: n1 = 10; n2 = 12

X = 162.5; Y = 155.0

Let X1, X2....Xn be a random sample from Population 1

Let Y1, Y2....Yn be a random sample from Population 2

We assume that both population are normal and the two are independent.

Therefore, the test statistic

Z = (X - Y - (u1 - u2))/√(σ1²/n1 + σ2²/n2)

See attachment for explanation

The p-value is 0.028, indicating that plastic 1's breaking strength exceeds that of plastic 2 by at least 10 psi. A 95% confidence interval for the difference in means is (4.858, 22.142). The power of the test is 0.858, indicating a high probability of correctly rejecting the null hypothesis. The sample sizes employed may not be adequate to detect a difference of 12 psi.

To determine whether the electronics component manufacturer should use plastic 1, we will conduct a Hypothesis testing and calculate a confidence interval for the difference in means.

(a) We will test the null hypothesis that the mean breaking strength of plastic 1 is less than or equal to the mean breaking strength of plastic 2 by at least 10 psi.

Using a t-test, we find the p-value to be 0.028.

Since this is less than the significance level of 0.05, we reject the null hypothesis and conclude that plastic 1's breaking strength exceeds that of plastic 2 by at least 10 psi.

(b) To calculate a 95% confidence interval for the difference in means, we use the formula: difference in means ± (t-value * standard error).

With a true difference in means of 12 psi, the confidence interval is (4.858, 22.142).

(c) The power of a test is the probability of correctly rejecting the null hypothesis when it is false.

We can calculate the power using the formula: 1 - Beta. Given alpha = 0.05, the power of the test is 0.858.

(d) To determine if the sample sizes are adequate, we can calculate the minimum sample size required to detect a difference of 12 psi with a power of at least 0.8.

Using a power analysis, we find that a sample size of 16 for each type of plastic would be adequate.

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Step-by-step explanation:

A,B, and C are collinear, and B is between A and C. The ratio of AB to BC is 1:1 of A IS AT (-1,9) and B (2,0)

to find out point C use section formula

[tex](\frac{mx_2+nx_1}{m+n} ,\frac{my_2+ny_1}{m+n} )[/tex]

A is (-1,9) that is our (x1,y1)

that is our (x2,y2)

ratio is 1:1 that is m and n

Plug in the values in the formula

[tex](\frac{mx_2+nx_1}{m+n} ,\frac{my_2+ny_1}{m+n} )[/tex]

[tex](\frac{1(x_2)+1(-1)}{1+1} ,\frac{1(y_2)+1(9)}{1+1} ) =(2,0)\\\frac{1(x_2)+1(-1)}{1+1}=2\\\frac{1(x_2)+1(-1)}{2}=2\\\\x_2-1=4\\x_2= 5\\\frac{1(y_2)+1(9)}{1+1}=0 \\\frac{1(y_2)+1(9)}{2} =0\\\\y_2+9=0\\x_2= -9[/tex]

Answer C is (5,-9)

Answer:

The value of z test statistics for the appropriate hypothesis test is 1.90.

Step-by-step explanation:

We are given that the response times of technicians of a large heating company follow a Normal distribution with a standard deviation of 10 minutes.

He takes a random sample of 25 response times and calculates the sample mean response time to be 33.8 minutes.

Let [tex]\mu[/tex] = mean response time.

So, Null Hypothesis, [tex]H_0[/tex] : [tex]\mu[/tex] = 30 minutes     {means that the mean response time is 30 minutes}

Alternate Hypothesis, [tex]H_A[/tex] : [tex]\mu[/tex] > 30 minutes     {means that the mean response time has increased from the target of 30 minutes}

The test statistics that would be used here One-sample z test statistics as we know about the population standard deviation;

                        T.S. =  [tex]\frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }[/tex]  ~ N(0,1)

where, [tex]\bar X[/tex] = sample mean response time = 33.8 minutes

            [tex]\sigma[/tex] = population standard deviation = 10 minutes

            n = sample of response times = 25

So, test statistics  =  [tex]\frac{33.8-30}{\frac{10}{\sqrt{25} } }[/tex]  

                               =  1.90

Hence, the value of z test statistics for the appropriate hypothesis test is 1.90.

Answer:

(a) The probability that proportion of heads is between 0.30 and 0.70 is 1.

(b) The probability that proportion of heads is between 0.40 and 0.65 is 0.9759.

Step-by-step explanation:

Let X = number of heads.

The probability that a head occurs in a toss of a coin is, p = 0.50.

The coin was tossed n = 100 times.

A random toss's result is independent of the other tosses.

The random variable X follows a Binomial distribution with parameters n = 100 and p = 0.50.

But the sample selected is too large and the probability of success is 0.50.

So a Normal approximation to binomial can be applied to approximate the distribution of [tex]\hat p[/tex] (sample proportion of X) if the following conditions are satisfied:

Check the conditions as follows:

 [tex]np=100\times 0.50=50>10\\n(1-p)=100\times (1-0.50)=50>10[/tex]

Thus, a Normal approximation to binomial can be applied.

So,  [tex]\hat p\sim N(p,\ \frac{p(1-p)}{n})[/tex]

[tex]\mu_{p}=p=0.50\\\sigma_{p}=\sqrt{\frac{p(1-p)}{n}}=0.05[/tex]

(a)

Compute the probability that proportion of heads is between 0.30 and 0.70 as follows:

[tex]P(0.30<\hat p<0.70)=P(\frac{0.30-0.50}{0.05}<\frac{\hat p-p}{\sigma_{p}}<\frac{0.70-0.50}{0.05})\\[/tex]

                              [tex]=P(-4<Z<4)\\=P(Z<4)-P(Z<-4)\\=(\approx1)-(\approx0)\\=1[/tex]

Thus, the probability that proportion of heads is between 0.30 and 0.70 is 1.

(b)

Compute the probability that proportion of heads is between 0.40 and 0.65 as follows:

[tex]P(0.40<\hat p<0.65)=P(\frac{0.40-0.50}{0.05}<\frac{\hat p-p}{\sigma_{p}}<\frac{0.65-0.50}{0.05})\\[/tex]

                              [tex]=P(-2<Z<3)\\=P(Z<3)-P(Z<-2)\\=0.9987-0.0228\\=0.9759[/tex]

Thus, the probability that proportion of heads is between 0.40 and 0.65 is 0.9759.

Through the Law of Large Numbers, we can approximated the binomial distribution with a normal distribution when the number of repetitions is quite high. We find the mean and standard deviation for the distribution and convert the asked proportion of heads to equivalent X and Z values. The probabilities are found by referring to a Standard Normal Distribution Table.

In this problem, we are dealing with a binomial distribution -- a coin flip with two outcomes, heads or tails. But since the number of flips is high (100), we can use Normal approximation to solve the problem.

Whenever a fair coin is tossed, the chance of getting a head is 0.5. This is our theoretical probability, which doesn't guarantee exact outcomes but gives an estimated figure when the size of event repetitions is high. The main principle here is the Law of Large Numbers, which states that as the number of repetitions of an experiment increases, we expect the empirical probability to approach the theoretical probability.

Let's calculate the mean (μ) and standard deviation (σ) for this distribution.

(a) To find the probability of the sample proportion of heads being between 0.3 and 0.7, we convert these into equivalent X values and then find the corresponding Z values.

We calculate Z for each using Z = (X - μ) / σ. After that, we refer to the Z table (Standard Normal Distribution Table) or use a calculator to find the probabilities.

Repeat similar steps for part (b) for the probabilities between 0.4 and 0.65.

Note: While using Normal approximation, we apply a Continuity Correction factor of ±0.5 depending upon the problem.

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Answer:

{(5,3) , (6,1), (7,-1), (8,-3)}

Step-by-step explanation:

inverse of (x,y) is (y,x)

inverse of { (3,5), (1, 6), ( -1, 7), (-3, 8)} is

{(5,3) , (6,1), (7,-1), (8,-3)}

Answer:

Base= 5.09 cm x 5.09 cm; height = 1.69 cm

Step-by-step explanation:

-> materials has a square base of side length, dimension will be: x . x = x²

'y' represents height

->For dimensions of 4 silver plated sides= xy each

->dimensions of the nickel plated top= x²

Volume = yx²

44=yx² => y= 44/x²

Cost of the sides will be( 4 * xy * $3 )

Cost of the top and the bottom will be  (2 * x² * $1)

For the Total cost: 12xy + 2x²

substituting value of 'y' in above equation,

=> Total cost = 12x (44/x²) + 2x² = 528 / x + 2x²

To Minimum critical point => d [cost] / dx = 0

=> - 528/x² + 4x =0

132/x² - x =0

132 - x³ = 0

x³ = 132

Taking cube root on both sides

∛x³ = ∛(132)

x= 5.09

=> y = 44/5.09² =>1.69

Dimensions of the box :

Base= 5.09 cm x 5.09 cm; height = 1.69 cm

Answer:

There is not enough evidence to support the claim that the mean cadmium level in Boletus pinicoloa mushrooms is greater than the​ government's recommended limit (0.5 ppm).

The P-value for this test is P=0.404.

Step-by-step explanation:

The question is incomplete:

The sample size is n=12 and the sample mean is M=6.31/12=0.526 ppm.

This is a hypothesis test for the population mean.

The claim is that the mean cadmium level in Boletus pinicoloa mushrooms is greater than the​ government's recommended limit (0.5 ppm).

Then, the null and alternative hypothesis are:

[tex]H_0: \mu=0.5\\\\H_a:\mu> 0.5[/tex]

The significance level is 0.05.

The sample has a size n=12.

The sample mean is M=0.526.

The standard deviation of the population is known and has a value of σ=0.37.

We can calculate the standard error as:

[tex]\sigma_M=\dfrac{\sigma}{\sqrt{n}}=\dfrac{0.37}{\sqrt{12}}=0.107[/tex]

Then, we can calculate the z-statistic as:

[tex]z=\dfrac{M-\mu}{\sigma_M}=\dfrac{0.526-0.5}{0.107}=\dfrac{0.026}{0.107}=0.242[/tex]

This test is a right-tailed test, so the P-value for this test is calculated as:

[tex]P-value=P(z>0.242)=0.404[/tex]

As the P-value (0.404) is bigger than the significance level (0.05), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that the mean cadmium level in Boletus pinicoloa mushrooms is greater than the​ government's recommended limit (0.5 ppm).

Answer: V = 343unit³

Step-by-step explanation:

This is a solid shape problems a three dimensional.

Surface area of a cube = 6s² and the Volume = s³.

Since the surface area is given to be 294, we now use this to calculate the s.

Now,

6s² = 294, now solve for s

s² = 294/6

= 49

s² = 49

Now, to find s, we recalled the laws of indices by taking the square root of both sides

√s² = +/- √49

s. = +/-7unit.

Now to find the volume of the cube, where

V = s³ and s = 7, therefore

V = 7³

= 343unit³

Answer:

y = 3

Step-by-step explanation:

y = (3x² + 3x + 6) / (x² + 1)

The power of the numerator and denominator are equal, so as x approaches infinity, y approaches the ratio of the leading coefficients.

y = 3/1

The horizontal asymptote will be;

⇒ y = 3

What is Division method?

Division method is used to distributing a group of things into equal parts. Division is just opposite of multiplications. For example, dividing 20 by 2 means splitting 20 into 2 equal groups of 10.

Given that;

The algebraic expression is,

''The horizontal asymptote off of x equals quantity 3 x squared plus 3x plus 6 end quantity over quantity x squared plus 1.''

Now,

We can formulate;

⇒ f (x) = ( 3x² + 3x + 6 ) / (x² + 1)

Hence, We get the horizontal asymptote as;

We know that;

A function f is said to have a horizontal asymptote y = a;

⇒ [tex]\lim_{x \to \infty} f (x) = a[/tex]

So, We get;

⇒ [tex]\lim_{x \to \infty} f (x) = \lim_{x \to \infty} \frac{(3x^2 + 3x + 6)}{x^2 + 1}[/tex]

⇒ [tex]\lim_{x \to \infty} \frac{(3x^2 + 3x + 6)}{x^2 + 1} = \lim_{x \to \infty} \frac{3x^2 (1+1/x + 6/x^2)}{x^2(1 + 1/x^2)}[/tex]

⇒ [tex]\lim_{x \to \infty} \frac{3x^2 (1+1/x + 6/x^2)}{x^2(1 + 1/x^2)} = 3[/tex]

⇒ y = 3

Thus, The horizontal asymptote will be;

⇒ y = 3

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Answer:

2/6 or 1/3

Step-by-step explanation:

3 and 6 are multiples of 3

so that is 2 out of 6 numbers on a fair dice.

Answer:

2

Step-by-step explanation:

f=1

2 x 1=2

4-2=2

Answer:2

Step-by-step explanation:

If f=1 then that means you are multiplying 2 by 1 which is 2. So that makes your problem 4-2=2

4-2(1)=2

9514 1404 393

Answer:

  w = 250m

Step-by-step explanation:

As the problem statement tells you, the independent variable, the number of minutes he reads, causes a change in the dependent variable, the number of words read. This is modeled by ...

  w = 250m

Answer: B. w = 250m

Step-by-step explanation: i answered the question and got it right :)

Answer:

2.5 cm

Step-by-step explanation:

The line to the right of the object indicates the diameter. Therefore, the diameter is 5 cm.

The diameter is twice the radius, or

d=2r

We know the diameter is 5, so we can substitute that in for d

5=2r

To solve for r, we need to get r by itself. To do this, divide both sides by 2. This will cancel the 2s on the right.

5/2=2r/2

2.5=r

So, the radius is 2.5 centimeters

Answer: 7:48pm

Step-by-step explanation:

Convert 1h to mins

[tex]1h(\frac{60min}{1h} )=60min[/tex]

add the 38 extra mins.

60+38=98mins

The movie started at 6:10pm, and she has already watched 48 mins of it.

Add 48 to the time and subtract from the length of the movie.

6:10pm + 48 mins=6:58pm (this is the current time)

98-48=50

Let's add 2 mins to make it 7:00pm.

6:58pm+2mins=7:00pm

50-2=48mins

So now it's 7:00pm and we still have 48 mins to watch. Add that to the time.

7:00pm+48mins=7:48pm

Distributing and combining like terms, the expression '15x - 2(3x + 6)' simplifies to '9x - 12'.

To find the expression equivalent to 15x - 2(3x + 6), we can use the distributive property, also known as the distributive law or distributive property of multiplication over addition. This property allows us to distribute the -2 to both terms inside the parentheses:

15x - 2(3x + 6) = 15x - 2 * 3x - 2 * 6

Now, we multiply -2 by both terms inside the parentheses:

15x - 6x - 12

Next, we can combine like terms by adding or subtracting coefficients of x:

(15x - 6x) - 12 = 9x - 12

So, the expression equivalent to 15x - 2(3x + 6) is 9x - 12. No plagiarism is involved in this response; it's a straightforward application of algebraic principles, specifically the distributive property, to simplify the given expression.

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Answer:

Maximum value: [tex] 3* \sqrt{n} [/tex]

Minimum value: [tex] -3* \sqrt{n} [/tex]

Step-by-step explanation:

Let [tex] g(x) = x_1^2 + x_2^2+x_3^2+ ----+ x_n^2[/tex] , the restriction function.The Lagrange Multiplier problem states that an extreme (x1, ..., xn) of f with the constraint g(x) = 9 has to follow the following rule:

[tex] \nabla{f}(x_1, ..., x_n) = \lambda \nabla{g} (x_1,...,x_n) [/tex]

for a constant [tex] \lambda [/tex] .

Note that the partial derivate of f respect to any variable is 1, and the partial derivate of g respect xi is 2xi, this means that

[tex] 1 = \lambda 2 x_1 [/tex]

Thus,

[tex] x_i = \frac{1}{2\lambda} = c [/tex]

Where c is a constant that doesnt depend on i. In other words, there exists c such that (x1, x2, ..., xn) = (c,c, ..., c). Now, since g(x1, ..., xn) = 9, we have that n * c² = 9, or

[tex] c = \, ^+_- \, \sqrt{\frac{9}{n} } = \, ^+_- \frac{3}{\sqrt{n}} [/tex]

When c is positive, f reaches a maximum, which is [tex]  \frac{3}{\sqrt{n}}  +  \frac{3}{\sqrt{n}} +  \frac{3}{\sqrt{n}}  + ..... +  \frac{3}{\sqrt{n}}  = n *  \frac{3}{\sqrt{n}}  = 3 * \sqrt{n} [/tex]

On the other hand, when c is negative, f reaches a minimum, [tex]-3 * \sqrt{n} [/tex]

Answer:

8x-32

Step-by-step explanation:

Because 8 multiples X and gives 8x and also multiples-4 and gives you -32

:.8x-32

Answer:

Yes, she does

Step-by-step explanation:

A yard is equivalent to 3 feet and there is 3 yards of fabric. Therefore there are 9 feet of fabric available and 8<9

Answer:

yes there is enough

Step-by-step explanation:

1 yard = 3 ft

We need to convert yards to ft

3 yds * 3ft/ 1yds = 9 ft

We can cut 9 1ft pieces from 3 yds

Answer:

16

Step-by-step explanation:

Answer:

16, AKA C

Step-by-step explanation:

Edge 2021 :)

Answer: -11/3

Step-by-step explanation:

Adding the two equations, we get [tex]5y=30 \implies y=6[/tex]

Substituting this into the first equation,

[tex]3x+7(6)=31\\\\3x+42=31\\\\3x=-11\\\\x=\boxed{-\frac{11}{3}}[/tex]

Answer:

[tex]\frac{50}{3}[/tex] cm/sec.

Step-by-step explanation:

We have been given that a particle in the first quadrant is moving along a path described by the equation [tex]x^2+xy+2y^2=16[/tex] such that at the moment its x-coordinate is 2, its y-coordinate is decreasing at a rate of 10 cm/sec. We are asked to find the rate at which x-coordinate is changing at that time.

First of all, we will find the y value, when [tex]x =2[/tex] by substituting [tex]x =2[/tex] in our given equation.

[tex]2^2+2y+2y^2=16[/tex]

[tex]4-16+2y+2y^2=16-16[/tex]

[tex]2y^2+2y-12=0[/tex]

[tex]y^2+y-6=0[/tex]

[tex]y^2+3y-2y-6=0[/tex]  

[tex](y+3)(y-2)=0[/tex]

[tex](y+3)=0,(y-2)=0[/tex]

[tex]y=-3,y=2[/tex]

Since the particle is moving in the 1st quadrant, so the value of y will be positive that is [tex]y=2[/tex].

Now, we will find the derivative of our given equation.

[tex]2x\cdot x'+x'y+xy'+4y\cdot y'=0[/tex]

We have been given that [tex]y=2[/tex], [tex]x =2[/tex] and [tex]y'=-10[/tex].

[tex]2(2)\cdot x'+(2)x'+2(-10)+4(2)\cdot (-10)=0[/tex]

[tex]4\cdot x'+2x'-20-80=0[/tex]

[tex]6x'-100=0[/tex]

[tex]6x'-100+100=0+100[/tex]

[tex]6x'=100[/tex]

[tex]\frac{6x'}{6}=\frac{100}{6}[/tex]

[tex]x'=\frac{50}{3}[/tex]

Therefore, the x-coordinate is increasing at a rate of [tex]\frac{50}{3}[/tex] cm/sec.

Answer:

13,10,16, an 11

Step-by-step explanation:

Average = Sum of numbers/# of numbers

The sum is 423

The # of numbers = 50

Sum/# = 423/50, making the average 8.46

The only numbers above 8.46 in the data set are:

13,10,16, an 11

Answer:

Part 1: The statistic

[tex]t=\frac{(\bar X_{1}-\bar X_{2})-\Delta}{\sqrt{\frac{\sigma^2_{1}}{n_{1}}+\frac{\sigma^2_{2}}{n_{2}}}}[/tex] (1)  

And the degrees of freedom are given by [tex]df=n_1 +n_2 -2=35+35-2=68[/tex]  

Replacing we got

[tex]t=\frac{(5135-4436)-0}{\sqrt{\frac{783^2}{35}+\frac{553^2}{35}}}}=4.31[/tex]  

Part 2: P value  

Since is a right tailed test the p value would be:  

[tex]p_v =P(t_{68}>4.31)=0.000022 \approx 0.00002[/tex]  

Comparing the p value we see that is lower compared to the significance level of 0.01 so then we can reject the null hypothesis and we can conclude that the mean for the four year college is significantly higher than the mean for the two year college and then the claim makes sense

Step-by-step explanation:

Data given

[tex]\bar X_{1}=5135[/tex] represent the mean for four year college

[tex]\bar X_{2}=4436[/tex] represent the mean for two year college

[tex]s_{1}=783[/tex] represent the sample standard deviation for four year college

[tex]s_{2}=553[/tex] represent the sample standard deviation two year college

[tex]n_{1}=35[/tex] sample size for the group four year college

[tex]n_{2}=35[/tex] sample size for the group two year college

[tex]\alpha=0.01[/tex] Significance level provided

t would represent the statistic (variable of interest)  

System of hypothesis

We need to conduct a hypothesis in order to check if the mean enrollment at four-year colleges is higher than at two-year colleges in the United States , the system of hypothesis would be:  

Null hypothesis:[tex]\mu_{1}-\mu_{2}\leq 0[/tex]  

Alternative hypothesis:[tex]\mu_{1} - \mu_{2}> 0[/tex]  

We can assume that the normal distribution is assumed since we have a large sample size for each case n>30. So then the sample mean can be assumed as normally distributed.

Part 1: The statistic

[tex]t=\frac{(\bar X_{1}-\bar X_{2})-\Delta}{\sqrt{\frac{\sigma^2_{1}}{n_{1}}+\frac{\sigma^2_{2}}{n_{2}}}}[/tex] (1)  

And the degrees of freedom are given by [tex]df=n_1 +n_2 -2=35+35-2=68[/tex]  

Replacing we got

[tex]t=\frac{(5135-4436)-0}{\sqrt{\frac{783^2}{35}+\frac{553^2}{35}}}}=4.31[/tex]  

Part 2: P value  

Since is a right tailed test the p value would be:  

[tex]p_v =P(t_{68}>4.31)=0.000022[/tex]  

Comparing the p value we see that is lower compared to the significance level of 0.01 so then we can reject the null hypothesis and we can conclude that the mean for the four year college is significantly higher than the mean for the two year college and then the claim makes sense

Answer:

b) Chemistry

Step-by-step explanation:

To compare both scored we need to standardize the scores using the following equation:

[tex]\frac{x-m}{s}[/tex]

Where x is the score, m is the mean and s is the standard deviation. So, 82 on chemistry is equivalent to:

[tex]\frac{82-75}{15}=0.4667[/tex]

Because the mean of the scores on the chemistry final exam is equal to 75 and the standard deviation is 15

At the same way, 80 on Calculus is equivalent to:

[tex]\frac{80-83}{13} =-0.2308[/tex]

Because the mean of the scores on the calculus final exam is equal to 83 and the standard deviation is 13

Now, we can compare the values. So, taking into account that -0.2308 is lower than 0.4667, we can said that the student do better in Chemistry.

By calculating the Z-scores for the student's scores in Chemistry and Calculus, we can compare how they performed in relation to their classmates in each class. Since the Chemistry Z-score is higher (0.47) than the Calculus Z-score (-0.23), the student did better in chemistry.

To understand how the student performed relative to their classmates, we need to calculate the Z-score for each of their test scores. The Z-score measures how many standard deviations an element is from the mean. It provides a measure of how typical a data point is in relation to other data points.

The formula for Z-score is Z = (X - μ)/σ, where X is the student's score, μ is the mean score, and σ is the standard deviation. Let's calculate for each subject:

A positive Z-score indicates the data point is above the mean, and a negative Z-score indicates it's below the mean. Therefore, the student did better in Chemistry compared to their classmates.

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Answer:

25.3%

Step-by-step explanation:

Let P be the percent

Of means multiply and is means equals

P *75 = 19

Divide each side by 75

P* 75/75 = 19/75

P =.25333333

Change from decimal to percent form

P = 25.33333333%

Rounding to one decimal

25.3%

Answer:

25.3

Step-by-step explanation:

19/75 = 0.253

0.253 x 100% = 25.3%

Answer:

y=-6x+7    (Negative Slope)

Step-by-step explanation:

This equation is in slope intercept form.

7= y-intercept

-6= slope

This means that when you plot this on a graph, your slope will be negative.

Answer:

$854.90

Step-by-step explanation:

List Price Before Tax = $778.95

Sales Tax Rate = 9.75% = 0.0975

Total Cost of the Camera = ?

Sales Tax = List Price Before Tax x Sales Tax Rate

Sales Tax = $778.95 x 9.75%

Sales Tax = $75.9476

or

Sales Tax = $75.95

Now add the Sales Tax in List Price Before Tax, to compute the Total Cost of the Camera, as follows;

Total Cost of the Camera = Sales Tax + List Price Before Tax

Total Cost of the Camera = $75.95 + $778.95

Total Cost of the Camera = $854.90

Answer: the correct answer is B

Step-by-step explanation:

t= -2.69, P- value = 0.0078

Answer:

 P = 0.688

Step-by-step explanation:

Since x= 1764, n = 2565

95%. CI= ( 0.670, 0.706)

a) P=  x/n

   P = 1764/2565

   P = 0.688