2 number cubes are rolled
what is the probability that the first lands on an odd number and the second lands on an even number? ​

Answer:

There is a probability of 86.6% that the sample mean falls within 0.03 percent of the raw purity mean.

Step-by-step explanation:

We have a population standard deviation of σ ≈ 0.1.

We have a sample of size n=25.

Then, we have a sampling distribution, which has a standard deviation for the sample mean that is:

[tex]\sigma_s=\dfrac{\sigma}{\sqrt{n}}=\dfrac{0.1}{\sqrt{25}}=\dfrac{0.1}{5}=0.02[/tex]

Now, we can calculate a z-score for a deviation of 0.03 percent from the mean as:

[tex]z=\dfrac{X-\mu}{\sigma}=\dfrac{0.03}{0.02}=\dfrac{0.03}{0.02}=1.5[/tex]

Note: we considered that the margin is ±0.03.

Then, the probability is:

[tex]P(|X-\mu|<0.03\%)=P(|z|<1.5)=0.866[/tex]

Answer:

B. Isosceles triangle

Answer: obtuse and isosceles <3

Step-by-step explanation:

Answer:

P(odd number) = 0.5

Step-by-step explanation:

There are 90 members in the set (10, 11, 12, .. , 97, 98, 99)

When we have an even number of consecutive numbers, the number of even numbers equals the number of odd numbers. This means that half of the numbers in this set are even and half of them are odd.

So the probability of P(odd number) = 0.5

Answer:

a. In the explanation.

b. The point estimate of the difference can be calculated as the difference between the sample mean and the population mean:

[tex]d=M-\mu=24.95-23.8=1.15[/tex]

c. Test statistic t = 0.90

P-value = 0.1932

The null hypothesis failed to be rejected.

Step-by-step explanation:

We have a sample, wich mean and standard deviation are calculated as:

[tex]M=\dfrac{1}{14}\sum_{i=1}^{14}(27.8+23.84+25.25+21+17.52+19.61+...+26.94+27.24)\\\\\\ M=\dfrac{349.34}{14}=24.95[/tex]

[tex]s=\sqrt{\dfrac{1}{(n-1)}\sum_{i=1}^{14}(x_i-M)^2}\\\\\\s=\sqrt{\dfrac{1}{13}\cdot [(27.8-(24.95))^2+(23.84-(24.95))^2+...+(27.24-(24.95))^2]}\\\\\\s=\sqrt{\dfrac{1}{13}\cdot [(8.106)+(1.238)+...+(5.23)]}\\\\\\ s=\sqrt{\dfrac{304.036}{13}}=\sqrt{23.39}\\\\\\s=4.8[/tex]

This is a hypothesis test for the population mean.

The claim is that the consumption of milk in the Midwest is significantly higher than the national average.

Then, the null and alternative hypothesis are:

[tex]H_0: \mu=23.8\\\\H_a:\mu> 23.8[/tex]

The significance level is 0.01.

The sample has a size n=14.

The sample mean is M=24.95.

As the standard deviation of the population is not known, we estimate it with the sample standard deviation, that has a value of s=4.8.

The estimated standard error of the mean is computed using the formula:

[tex]s_M=\dfrac{s}{\sqrt{n}}=\dfrac{4.8}{\sqrt{14}}=1.28[/tex]

Then, we can calculate the t-statistic as:

[tex]t=\dfrac{M-\mu}{s/\sqrt{n}}=\dfrac{24.95-23.8}{1.28}=\dfrac{1.15}{1.28}=0.9[/tex]

The degrees of freedom for this sample size are:

[tex]df=n-1=14-1=13[/tex]

This test is a right-tailed test, with 13 degrees of freedom and t=0.9, so the P-value for this test is calculated as (using a t-table):

[tex]\text{P-value}=P(t>0.9)=0.1932[/tex]

As the P-value (0.1932) is bigger than the significance level (0.01), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that the consumption of milk in the Midwest is significantly higher than the national average.

Answer: The value is 18.

Step-by-step explanation:

Since we already know what p, q, and r equal, we can use what we know and plug in the numbers:

p=7, q=5, and r=3,

p2=7*2=14

q2=5*2=10

r2=3*2=6

In conclusion, 14+10-6=18

The value of p2+q2-r2 is 18.

Answer:

Just simply change the variables with their values

7 x 2 + 5 x 2 - 3 x 2

14 + 10 - 6

24 - 6 = 18

18 is the answer

Hope this helps

Step-by-step explanation:

Answer:

Associative property of multiplication is the grouping of numbers being multiplied can be changed without affecting the product.

here is an example!

Addison Rae work using the associative property:

(-8.5)(5)(-4) =

(-8.5)(-20) =

170

hope this helped it was from my FLVS schooling :)

Answer:

Step-by-step explanation:

Hello!

The sample shows the scores for the combined three-part SAT.

Raw data in first attachment.

a.

To arrange the data in a frequency table using class intervals you have to determine the number of intervals you want to use and calculate their width. In this case, the width is given and so is the lower limit of the first interval, you calculate the successive limits by adding the width. The lower limit of the next interval will be the upper limit of the previous one:

1) 800 + 200= 100

First interval [800; 1000)

2) 1000 + 200

Second interval

[1000; 1200)

And so on until you reach the maximum value of the data set,

[1200; 1400)

[1400; 1600)

[1600; 1800)

[1800; 2000)

[2000; 2200)

Then you have to order the data from least to greatest and count how many observations correspond to each value, this way you'll determine the observed frequency for each interval.

Table and histogram in second attachment.

b.

As you can see in the histogram, this distribution is symmetrical centered in the interval [1400; 1600) and there are no outliers observed.

c.

Values around 1400-1600 are the most common ones while scores around 800-1000 or 2000-2200 are more uncommon, in this sample it seems the probability to obtain a perfect score for the combined three-part SAT is extremely low.

I hope you have a nice day!

Answer:

y=-5/2x-1

Step-by-step explanation:

first find the gradient whereas since the two lines are parallel they hav the same gradient. y=mx+c whereas m is the gradient. 5x+2y=12

2y=-5x+12

y=-5/2x+12(so the gradient is -5/2x..... gradient=-5/2

y-4=-5/2

x+2

y-4=-5/2(x+2)

y-4=-5/2x-5

y=-5/2x-5+4

y=-5/2x-1

The equation of the line that is parallel to the line 5x + 2y = 12 and passes through the point (-2, 4) is y = -5/2 x - 1.

Equation of a line in slope intercept form is y = mx + b, where m is the slope of the line and b is the y intercept, which is the y coordinate of the point where it touches the Y axis.

Given that the equation of the line is,

5x + 2y = 12

2y = -5x + 12

y = -5/2 x + 6

This is in the slope intercept form, where the slope = -5/2.

Slopes of two parallel lines are equal.

So any line parallel to the given line will be of the form y = -5/2 x + c

Given line passes through (-2, 4).

Substituting (-2, 4) in y = -5/2 x + c, we get,

(-5/2) (-2) + c = 4

c = -1

So the equation is, y = -5/2 x - 1

Hence the required equation is y = -5/2 x - 1.

Learn more about Slope Intercept form here :

https://brainly.com/question/21298390

#SPJ7

Answer:  nice and funnyyyyy y=4

Step-by-step explanation:

Answer:

The correct option is (A).

Step-by-step explanation:

If the reduced row echelon form of the coefficient matrix of a linear system of equations in four different variables has a pivot, i.e. 1, in each column, then the reduced row echelon form of the coefficient matrix is say A is an identity matrix, here I₄, since there are 4 variables.

[tex]\left[\begin{array}{cccc}1&0&0&0\\0&1&0&0\\0&0&1&0\\0&0&0&1\end{array}\right][/tex]

Then the corresponding augmented matrix [ A|B] , where the matrix is the representation of the linear system is AX = B, must be:

[tex]\left[\begin{array}{ccccc}1&0&0&0&a\\0&1&0&0&b\\0&0&1&0&c\\0&0&0&1&d\end{array}\right][/tex]

Now the given linear system is consistent as the right most column of the augmented matrix is a linear combination of the columns of A as the reduced row echelon form of A has a pivot in each column.

Thus, the correct option is (A).

Answer:

5

Step-by-step explanation:

3(14+x) = 57

42 +3x = 57

3x = 15

x = 5

Answer:

46.7%

Step-by-step explanation:

Given:

Total number of students in Mrs. Verner's class = 15

Number of girls = 8

To find: percentage are boys

Solution:

Percentage of boys = ( Number of boys / Total number of students ) × 100

Number of boys = Total number of students - Number of girls = 15 - 8 = 7

So,

Percentage of boys = [tex]\frac{7}{15}[/tex] × 100 = 46.7%

Answer:

[tex]y-x = 16[/tex]

Step-by-step explanation:

Given

Set 1: (9,5,y,2,x)

Set 2: (8,x,4,1,3)

Required

(y - x)

First the mean values of set 1 and set 2 has to be calculated

For set 1

[tex]Mean _1 = \frac{(9+5+y+2+x)}{5}[/tex]

Collect like terms

[tex]Mean _1 = \frac{9+5+2+y+x}{5}[/tex]

[tex]Mean _1 = \frac{16+ y+x}{5}[/tex]

For set 2

[tex]Mean _2 = \frac{(8+x+4+1+3)}{5}[/tex]

Collect like terms

[tex]Mean _2 = \frac{8+4+1+3+x}{5}[/tex]

[tex]Mean _2= \frac{16+ x}{5}[/tex]

Given that the mean of set 1 is twice the mean of set 2;

[tex]Mean_1 = 2Mean_2[/tex]

[tex]\frac{16+ y+x}{5} =2 * \frac{16+x}{5}[/tex]

Multiply both sided by 5

[tex]5 * \frac{16+ y+x}{5} = 5 * 2 * \frac{16+x}{5}[/tex]

[tex]16+ y+x = 2 * (16+x)[/tex]

Open bracket

[tex]16+ y+x = 32 + 2x[/tex]

Subtract 16 from both sides

[tex]16+ y+x- 16 = 32 + 2x - 16[/tex]

[tex]16 - 16 + y+x = 32 - 16 + 2x[/tex]

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

Subtract 2x from both sides

[tex]y+x-2x = 16 + 2x-2x[/tex]

[tex]y-x = 16[/tex]

Answer:

A. Observational study

Step-by-step explanation:

In research, an observational study is a type of study in which the researcher observes a phenomenon and tries to establish some relationship between the different variables he/she is observing. In other words, the researcher only observes and doesn't give a treatment.

On the other hand, when we have a experiment, we usually have 2 different groups (one that will receive a treatment and one who won't) and the researcher compares the differences between these two groups because of the treatment. In other words, the researcher does something other than just observing.

In this example, the research is going to determine if there is a relation between hearing loss and exposure to mumps. In this example the researcher is only going to observe how people who have been exposed to mumps are regarding hearing loss (we can say this since it will be unethical for example for the researcher to create an experiment in which he/she exposes a group to mumps). Therefore, he is going to observe how the past exposure to mumps could be related with the hearing loss.

Thus, this is an observational study.

Answer:

  the least common denominator

Step-by-step explanation:

The least common denominator is that number. It is the least common multiple of the denominator values.

__

Simply multiplying by the product of the denominators will eliminate fractions, but may require reduction of fractions in the answer. If the "fractions" are rational expressions, extraneous solutions may be introduced.

Answer:

see below

Step-by-step explanation:

i is the imaginary number and it represents the square root of -1

Answer:

[tex]y^2+88y+484[/tex]

Step-by-step explanation:

[tex]4(y+11)^2-3y^2= \\\\4(y^2+22y+121)-3y^2= \\\\4y^2-3y^2+88y+484= \\\\y^2+88y+484[/tex]

Hope this helps!

Answer:

A whole number that can be made by multiplying other whole numbers.

Example: 18 can be made by 3 × 6 so is a composite number.

16 can be made by 4 x 4 so it is a square root and a composite number

14 can be made by 2 x 7 so is is a composite number.

It is not a prime number as all Composite Number have factors other than 1 and itself). The first few composite numbers (sometimes called "composites" for short) are 4, 6, 8, 9, 10, 12, 14, 15, 16,

Answer:

We need to examine the natural numbers.

The natural numbers are the counting numbers,

1, 2, 3, 4, 5, 6, ...

The number 1 is neither prime nor composite.

All natural numbers greater than 1 are either prime or composite.

A prime number is a number that has exactly two factors, itself and 1.

A composite number has more than 2 factors.

A composite number is a natural number greater than 2 that is not a prime number.

Examples:

Prime: 2, 3, 5, 7, 11, ...

Composite: 4, 6, 8, 9, 10, 12, ...

Answer:

a) The probability that fewer than five of them have type o negative blood is 0.1275

b) The probability that fewer than five of them have type o negative blood is 0.9933

c) 0.2708 probability of no donors with type o negative blood. This probability is higher than 0.05, so it would not be unusual having none of the donors with type o negative blood.

Step-by-step explanation:

For each person, there are only two possible outcomes. Either they have type o negative blood, or they do not. The probability of a person having type o negative blood is independent of any other person. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

[tex]P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}[/tex]

In which [tex]C_{n,x}[/tex] is the number of different combinations of x objects from a set of n elements, given by the following formula.

[tex]C_{n,x} = \frac{n!}{x!(n-x)!}[/tex]

And p is the probability of X happening.

7% of U.S. residents have type o negative blood.

This means that [tex]p = 0.07[/tex]

18 donors.

This means that [tex]n = 18[/tex]

(a) What is the probability that three or more of them have type o negative blood?

Either less than three have, or at least three do. The sum of the probabilities of these events is 1. So

[tex]P(X < 3) + P(X \geq 3) = 1[/tex]

We want [tex]P(X \geq 3)[/tex]

So

[tex]P(X \geq 3) = 1 - P(X < 3)[/tex]

In which

[tex]P(X < 3) = P(X = 0) + P(X = 1) + P(X = 2)[/tex]

[tex]P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}[/tex]

[tex]P(X = 0) = C_{18,0}.(0.07)^{0}.(0.93)^{18} = 0.2708[/tex]

[tex]P(X = 1) = C_{18,1}.(0.07)^{1}.(0.93)^{17} = 0.3669[/tex]

[tex]P(X = 2) = C_{18,2}.(0.07)^{2}.(0.93)^{16} = 0.2348[/tex]

[tex]P(X < 3) = P(X = 0) + P(X = 1) + P(X = 2) = 0.2708 + 0.3669 + 0.2348 = 0.8725[/tex]

[tex]P(X \geq 3) = 1 - P(X < 3) = 1 - 0.8725 = 0.1275[/tex]

The probability that fewer than five of them have type o negative blood is 0.1275

(b) What is the probability that fewer than five of them have type o negative blood?

[tex]P(X < 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4)[/tex]

[tex]P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}[/tex]

[tex]P(X = 0) = C_{18,0}.(0.07)^{0}.(0.93)^{18} = 0.2708[/tex]

[tex]P(X = 1) = C_{18,1}.(0.07)^{1}.(0.93)^{17} = 0.3669[/tex]

[tex]P(X = 2) = C_{18,2}.(0.07)^{2}.(0.93)^{16} = 0.2348[/tex]

[tex]P(X = 3) = C_{18,3}.(0.07)^{3}.(0.93)^{15} = 0.0942[/tex]

[tex]P(X = 4) = C_{18,4}.(0.07)^{4}.(0.93)^{14} = 0.0266[/tex]

[tex]P(X < 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) = 0.2708 + 0.3669 + 0.2348 + 0.0942 + 0.0266 = 0.9933[/tex]

The probability that fewer than five of them have type o negative blood is 0.9933.

c) Would it be unusual f none of the donors had type o negative blood?

[tex]P(X = 0) = C_{18,0}.(0.07)^{0}.(0.93)^{18} = 0.2708[/tex]

0.2708 probability of no donors with type o negative blood. This probability is higher than 0.05, so it would not be unusual having none of the donors with type o negative blood.

Answer:

Step-by-step explanation:

The measure of an arc is twice the measure of the inscribed angle that subtends that arc. A tangent is a special case where the chord that is one leg of the inscribed angle has a length of zero.

1. Short arc LJ is 2a°. Short arc LK is 2b°. Then arc JLK is 2(a+b)°, and short arc JK is ...

  arc JK = 360° -2(a +b)° . . . . . matches choice B

__

2. Long arc WY is twice the measure of "inscribed" angle WYZ, so is ...

  long ard WY = 2(104°) = 208°

Then short arc WY is ...

  arc WXY = 360° -208° = 152°

__

3. The arc measures are double those of the corresponding inscribed angles. We can add up the arcs around the circle:

  (arc AB +arc BC) = 2×70° = 140° . . . inscribed angle relation

  (arc BC +arc CD) = 2×98° = 196° . . . inscribed angle relation

  arc AB + arc BC +arc CD +arc DA = 360° . . . . sum around the circle

Adding the first two equations with arc DA, we have ...

  (arc AB + arc BC) +(arc BC +arc CD) +arc DA = 360° +arc BC

  140° +196° +80° = 360° +arc BC

  416° -360° = arc BC = 56° . . . . . matches choice B

__

4. Angle C and angle A are supplementary in this inscribed quadrilateral.

  angle C = 180° -98° = 82° . . . . . matches choice A

Answer:

Step-by-step explanation:

Given that:

A small-business Web site contains 100 pages and 60%, 30%, and 10%  of the pages contain low, moderate, and high graphic content, respectively.

. A sample of four pages is selected without replacement,

Let  X and Y denote the number of pages with moderate and high graphics output in the sample

We are meant to determine

a)  [tex]f_{XY}(x, y)[/tex]  from the given data in the question;

However; the probability mass function can be expressed via the relation:

[tex]f_{XY}(x,y) = \dfrac{(^{30} _x ) ( ^{10} _y ) (^{60} _ {4-x-y} ) }{ ( ^{100}_4)}[/tex]

We can now have a table shown as :

[tex]X|Y[/tex]                0           1               2              3              4          Total    [tex]f_X(x)[/tex]

0              0.1244     0.0873     0.02031    0.0018     0.0001   0.234

1               0.2618     0.13542   0.02066    0.00092    0         0.419

2              0.1964     0.0666    0.00499       0              0         0.268

3              0.0621     0.01035     0                 0              0         0.073

4              0.0069       0              0                0              0          0.007

Total [tex]F_Y(y)[/tex]   0.6516   0.2996   0.0460      0.0028  0.0001    1

b) [tex]f_X(x)[/tex]

The marginal distribution definition of [tex]f_X(x)[/tex][tex]= P(X=x)[/tex]

[tex]f_X(x)[/tex] [tex]= \sum P(X=x, Y=y)[/tex]

From the table above ; the corresponding values of [tex]f_X(x)[/tex]  are :

X           0           1         2          3           4

[tex]f_X(x)[/tex]    0.234   0.419  0.268   0.073    0.007

( since [tex]f_X(x)[/tex] represent the vertical column)

c) E(X)

By using the expression [tex]E(x) = \sum ^4 _{x= 0} x f_X(x)[/tex]

we have:

E(X) = [tex]0*0.234+1*0.419+ 2*0.268+3*0.073+4*0.007[/tex]

E(X) = 0 + 0.419 + 0.536 + 0.218 + 0.028

E(X) = 1.202

d) fyß(y)

Using the thesis of conditional Probability; we have :

[tex]P(A|B) = \dfrac{ P(A,B) }{ P(B) }[/tex]

The conditional probability for the mass function is then:

[tex]f_{Y|X=3}(y) = \dfrac{f_{XY}(3,y)}{f_{X}(x)}[/tex]

where;

[tex]f_X(3) = 0.0725[/tex]

values of [tex]f_{XY} (3,y)[/tex] for every y ∈ (0,1,2,3,4)

Therefore; the mass function is:

[tex]Y|{_X_3}:\left[\begin{array}{ccccc}0&1&2&3&4\\0.857&0.143&0&0&0\\ \end{array}\right][/tex]

e) E(Y | X = 3)

By using the expression [tex]E(Y|X=3) = \sum ^4 _{y= 0} y f_{y \beta} \ (y|x)[/tex]

we have:

⇒ [tex]0 * 0.857 + 1*0.143 +0 +0+0[/tex]

= 0.143

The value of E(Y | X = 3) = 0.143

g) Are X and Y independent?

To Check if X and Y independent; Let assume if [tex]f_{XY}(x,y) = f_X(x)f_{Y}(y)[/tex] ; then we can say that X and Y are independent.

From the above previous table :

[tex]f_{(XY)} (0.4) = 0.0001[/tex]

[tex]f_X (0)[/tex] = 0.1244 + 0.087268+0.02031+ 0.001836 + 0.0001

[tex]f_X (0)[/tex]  = 0.234

[tex]f_X (4)=0.0001 +0+0 \\ \\ = 0.001[/tex]

[tex]f_{X}(0) f_Y(4) = 0.234*0.0001[/tex]

[tex]f_{X}(0) f_Y(4) = 0.00002[/tex]

We conclude that [tex]f_{(XY)} (0.4) \neq f_X(0) f_Y(y)[/tex]; As such X and Y are said to be  non - independent.

Answer:

Thats not possible

Step-by-step explanation:

There is no:

Answer:

The required probability is 0.4828.

Step-by-step explanation:

We are given that a company is producing two types of ski goggles. Thirty percent of the production is of type A, and the rest is of type B.

Five percent of all type A goggles are returned within 10 days after the sale, whereas only two percent of type B are returned.

Let the probability that production is of Type A = P(A) = 30%

Probability that production is of Type B = P(B) = 1 - P(A) = 1 - 0.30 = 70%

Also, let R = event that pair of goggles are returned

So, the probability that type A goggles are returned within 10 days after the sale = P(R/A) = 5%

Probability that type B goggles are returned within 10 days after the sale = P(R/B) = 2%  

Now, given a pair of goggles is returned within the first 10 days after the sale, the probability that the goggles returned are of type B is given by = P(B/R)

We will use the concept of Bayes' Theorem to calculate the above probability.

So,  P(B/R)  =  [tex]\frac{P(B) \times P(R/B)}{P(A) \times P(R/A)+P(B) \times P(R/B)}[/tex]

                   =  [tex]\frac{0.70 \times 0.02}{0.30 \times 0.05+0.70 \times 0.02}[/tex]

                   =  [tex]\frac{0.014}{0.029}[/tex]  =  0.4828

Answer:

The p-value obtained is less than the significance level at which the test was performed at, hence, we reject the null hypothesis, accept the alternative hypothesis & say that there is enough evidence to conclude that the the new medicine is potentially harmful.

Step-by-step explanation:

The null hypothesis plays the devil's advocate and usually takes the form of the opposite of the theory to be tested. It usually contains the signs =, ≤ and ≥ depending on the directions of the test.

While, the alternative hypothesis usually confirms the the theory being tested by the experimental setup. It usually contains the signs ≠, < and > depending on the directions of the test.

For this question, the null hypothesis is that the new medicine has no negative effects and the alternative hypothesis is that the new medicine is potentially harmful

Mathematically,

The null hypothesis is represented as

H₀: p = 0

The alternative hypothesis is represented as

Hₐ: p > 0

To do this test, we will use the z-distribution because although no information on the population standard deviation is known, the sample size is large enough.

So, we compute the test statistic

z = (x - μ)/σₓ

x = sample proportion = (31/3000) = 0.0103

μ = p₀ = 0

σₓ = standard error = √[p(1-p)/n]

where n = Sample size = 3000

σₓ = √[0.0103×0.9897/3000] = 0.0018462936 = 0.0018463

z = (0.0103 - 0) ÷ 0.0018463

z = 5.60

checking the tables for the p-value of this test statistic

Significance level = 1% = 0.01

The hypothesis test uses a one-tailed condition because we're testing only in one direction.

p-value (for z = 5.60, at 0.01 significance level, with a one tailed condition) = < 0.00001

The interpretation of p-values is that

When the (p-value > significance level), we fail to reject the null hypothesis and when the (p-value < significance level), we reject the null hypothesis and accept the alternative hypothesis.

So, for this question, significance level = 0.01

p-value = < 0.00001

p-value < 0.00001 < 0.10

Hence,

p-value < significance level

This means that we reject the null hypothesis, accept the alternative hypothesis & say that there is enough evidence to conclude that the the new medicine is potentially harmful.

Hope this Helps!!!

Answer:

Step-by-step explanation:

Corresponding net sales before 1 month and after 1 month form matched pairs.

The data for the test are the differences between the net sales before and after 1 month.

μd = the​ net sales before 1 month minus the​ net sales after 1 month.

Before after diff

57.1 63.5 - 6.4

94.6 101.8 - 7.2

49.2 57.8 - 8.6

77.4 81.2 - 3.8

43.2 41.9 1.3

Sample mean, xd

= (- 6.4 - 7.2 - 8.6 - 3.8 + 1.3)/5 = - 4.94

xd = - 4.94

Standard deviation = √(summation(x - mean)²/n

n = 5

Summation(x - mean)² = (- 6.4 + 4.94)^2 + (- 7.2 + 4.94)^2 + (- 8.6 + 4.94)^2+ (- 3.8 + 4.94)^2 + (1.3 + 4.94)^2 = 60.872

Standard deviation = √(60.872/5

sd = 3.49

For the null hypothesis

H0: μd ≥ 0

For the alternative hypothesis

H1: μd < 0

The distribution is a students t. Therefore, degree of freedom, df = n - 1 = 5 - 1 = 4

2) The formula for determining the test statistic is

t = (xd - μd)/(sd/√n)

t = (- 4.94 - 0)/(3.49/√5)

t = - 3.17

We would determine the probability value by using the t test calculator.

p = 0.017

Since alpha, 0.05 > than the p value, 0.017, then we would reject the null hypothesis. Therefore, at 5% significance level, the data indicate that the average net sales improved.

The transformation matrix for the mapping T is the matrix T such that

[tex]\mathbf T(\vec x)=T\,\vec x[/tex]

where

[tex]T=\begin{bmatrix}1&4&0&0\\0&0&0&0\\0&3&0&1\\0&1&0&-1\end{bmatrix}[/tex]

The correct matrix A is

[tex]A=\left[\begin{array}{cccc}1&4&0&0\\0&0&0&0\\0&3&0&1&0&1&0&-1\end{array}\right][/tex]

To find the matrix A that represents the linear transformation T, we need to determine the coefficients that map the input vector (X₁, X₂, X₃, X₄) to the output vector (x₁ +4x₂, 0, 3x₂ +x₄, x₂ -x₄)

By comparing the corresponding entries in the input and output vectors, we can determine the coefficients of the matrix A.

The first row of A will have the coefficients for X₁ and X₂, which are 1 and 4 respectively. The second row will have all zeros since the output vector has a zero in the second position. The third row will have the coefficient 3 for X₂ and 1 for X₄. Finally, the fourth row will have the coefficient 1 for X₂ and -1 for X₄.

Thus, the matrix A that implements the mapping T is:

[tex]A=\left[\begin{array}{cccc}1&4&0&0\\0&0&0&0\\0&3&0&1&0&1&0&-1\end{array}\right][/tex]

Learn more about linear transformation here:

brainly.com/question/13595405

#SPJ2

Answer: 1/20

Step-by-step explanation:

Decimal Fraction Percentage

0.05 1/20          5%

Answer:

Jaleel is correct because 2 (x + 2) = 2x - 4

Step-by-step explanation:

To solve 2 (x - 2) + 2:

2 (x - 2) + 2

Distribute

2x - 4 + 2

Combine like terms

2x - 2

Lisa did not distribute correctly :)

Answer:

D

Step-by-step explanation:

Answer:

The velocity is v(t) = 2*t + a

a) we want to find the average velocity betwen t = 0 and t = 1.

We can do this as:

Average = (v(1) + v(0))/2 = (2*1 + a + 2*0 + a)/2 = 1 + a

b) now we want to find the total distance traveled in the time lapse from t = 0 to t = 4.

For this we can see the integral:

[tex]d = \int\limits^4_0 {2*t + a} \, dt = 4^2 + a*4 - 0^2 - a*0 = 4^2 + a*4 = 16 + a^2[/tex]

Answer:

b. 4.9 × 1011

Step-by-step explanation:

Using scientific notation is similar to expressing in standard form. Given that (7 × 105)2

We open the parenthesis. This may first be expressed as

7² × 10⁽⁵⁾²

Then expand,

= 49 × 10¹⁰

To put in scientific notation, 49 = 4.9 × 10

Hence the expression becomes

= 4.9 × 10 × 10¹⁰

Using the laws of indices

= 4.9 ×  10¹¹ in scientific notation

Answer:

4.9 × 1011

Step-by-step explanation:

I did it in grandpoint