Ali is riding his bicycle. He rides at a Speed of 12.8 kilometers per hour for 2 hours how many kilometers did he ride

Tonisha must make $114 in daily sales to cover her $34 expenses and meet her $80 profit goal. This is a basic mathematics problem related to costs, revenues, and profits within a business context.

The subject of Tonisha’s lemonade stand involves determining the required earnings to achieve a certain profit goal, which falls under the subject of Mathematics. Specifically, it involves basic arithmetic and understanding of costs and revenues within a business context. To calculate how much Tonisha needs to make in sales to achieve her goal of at least $80 per day, we must add the expenses of $34 to the desired profit of $80. Therefore, Tonisha needs to make $114 per day in sales to cover expenses and meet her profit goal.

Answer:

a) [tex]P(X<3)=P(\frac{X-\mu}{\sigma}<\frac{3-\mu}{\sigma})=P(Z<\frac{3-5.1}{0.9})=P(z<-2.33)[/tex]

And we can find this probability using the normal standard table and we got:

[tex]P(z<-2.33)=0.010[/tex]

b) [tex]P(X>7)=P(\frac{X-\mu}{\sigma}>\frac{7-\mu}{\sigma})=P(Z>\frac{7-5.1}{0.9})=P(z>2.11)[/tex]

And we can find this probability using the complement rule and the  normal standard table and we got:

[tex]P(z>2.11)=1-P(Z<2.11) = 1-0.983 = 0.017[/tex]

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

Let X the random variable that represent the variable of interest of a population, and for this case we know the distribution for X is given by:

[tex]X \sim N(5.1,0.9)[/tex]  

Where [tex]\mu=5.1[/tex] and [tex]\sigma=0.9[/tex]

Part a

We are interested on this probability

[tex]P(X<3)[/tex]

And the best way to solve this problem is using the normal standard distribution and the z score given by:

[tex]z=\frac{x-\mu}{\sigma}[/tex]

If we apply this formula to our probability we got this:

[tex]P(X<3)=P(\frac{X-\mu}{\sigma}<\frac{3-\mu}{\sigma})=P(Z<\frac{3-5.1}{0.9})=P(z<-2.33)[/tex]

And we can find this probability using the normal standard table and we got:

[tex]P(z<-2.33)=0.010[/tex]

Part b

We are interested on this probability

[tex]P(X>7)[/tex]

And the best way to solve this problem is using the normal standard distribution and the z score given by:

[tex]z=\frac{x-\mu}{\sigma}[/tex]

If we apply this formula to our probability we got this:

[tex]P(X>7)=P(\frac{X-\mu}{\sigma}>\frac{7-\mu}{\sigma})=P(Z>\frac{7-5.1}{0.9})=P(z>2.11)[/tex]

And we can find this probability using the complement rule and the  normal standard table and we got:

[tex]P(z>2.11)=1-P(Z<2.11) = 1-0.983 = 0.017[/tex]

The standard matrix of the transformation T, resulting from a composition of the reflection through the vertical x2-axis and the reflection through the line x2 = x1, is: [ 0 -1 ] [ 1 0 ].

Find the standard matrix of the transformation T.

To do this, we can break the transformation T down into two simpler transformations:

Reflection through the vertical x2-axis: This transformation negates the x1 coordinate of each point while leaving the x2 coordinate unchanged. The standard matrix for this transformation is:

[ -1   0 ]

[  0   1 ]

Reflection through the line x2 = x1: This transformation swaps the x1 and x2 coordinates of each point. The standard matrix for this transformation is:

[ 0   1 ]

[ 1   0 ]

Since we are performing these transformations one after the other, we need to multiply the matrices together. The order of multiplication matters here, because matrix multiplication is not commutative. So, the standard matrix for the combined transformation T is:

[ 0   1 ]   [ -1   0 ]   =   [ 0 -1 ]

[ 1   0 ]   [  0   1 ]     [ 1  0 ]

Therefore, the standard matrix of the transformation T is:

[ 0 -1 ]

[ 1  0 ]

Complete question:

Assume that T is a linear transformation. Find the standard matrix of T.

​T:

set of real numbers R squaredℝ2right arrow→set of real numbers R squaredℝ2

first reflects points through the

vertical x 2 dash axisvertical x2-axis

and then reflects points through the

line x 2 equals x 1line x2=x1

The standard matrix of the linear transformation reflects points through the vertical axis and the line[tex]\(x_2 = x_1\) is \([-1\ 1\ 0\ 0]\).[/tex]

To find the standard matrix of the linear transformation  T , we need to determine the images of the standard basis vectors [tex]\( \mathbf{e}_1 \) and \( \mathbf{e}_2 \)[/tex] under  T .

First, let's understand the transformation described:

1. Reflection through the vertical [tex]\( x_2 \)[/tex]axis:

  This transformation replaces each point [tex]\( (x_1, x_2) \) with \( (-x_1, x_2) \).[/tex]

2. Reflection through the line [tex]\( x_2 = x_1 \):[/tex]

  This transformation replaces each point [tex]\( (x_1, x_2) \) with \( (x_2, x_1) \).[/tex]

To find the images of the standard basis vectors under  T :

- [tex]\( T(\mathbf{e}_1) \) is obtained by reflecting \( \mathbf{e}_1 = (1, 0) \) through the \( x_2 \) axis, resulting in \( (-1, 0) \).[/tex]

- [tex]\( T(\mathbf{e}_2) \) is obtained by reflecting \( \mathbf{e}_2 = (0, 1) \) through the line \( x_2 = x_1 \), resulting in \( (1, 0) \).[/tex]

Now, we can construct the standard matrix of  T  using the images of the standard basis vectors:

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

This matrix represents the transformation  T  as described.

The Complete Question:

Assume that T is a linear transformation. Find the standard matrix of T.

​T: set of real numbers R squaredℝ2right arrow→set of real numbers R squaredℝ2

first reflects points through the

vertical x 2 dash axisvertical x2-axis

and then reflects points through the

line x 2 equals x 1line x2=x1

Answer:

[tex]t=\frac{1.17-1.04}{\sqrt{\frac{0.11^2}{8}+\frac{0.09^2}{8}}}}=2.587[/tex]  

[tex]df=n_{1}+n_{2}-2=8+8-2=14[/tex]

Since is a one sided test the p value would be:

[tex]p_v =P(t_{(14)}>2.587)=0.0108[/tex]

If we compare the p value and the significance level given [tex]\alpha=0.05[/tex] we see that [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, we have enough evidence to reject the null hypothesis on this case and the 25 mil film have a mean greater than the 20 mil film so then the claim is not appropiate

Step-by-step explanation:

Data given and notation

[tex]\bar X_{1}=1.17[/tex] represent the mean for the sample 1 (25 mil film)

[tex]\bar X_{2}=1.04[/tex] represent the mean for the sample 2 (20 mil film)

[tex]s_{1}=0.11[/tex] represent the sample standard deviation for the sample 1

[tex]s_{2}=0.09[/tex] represent the sample standard deviation for the sample 2

[tex]n_{1}=8[/tex] sample size selected for 1

[tex]n_{2}=8[/tex] sample size selected for 2

[tex]\alpha=0.05[/tex] represent the significance level for the hypothesis test.

t would represent the statistic (variable of interest)

[tex]p_v[/tex] represent the p value for the test (variable of interest)

State the null and alternative hypotheses.

We need to conduct a hypothesis in order to check if reducing the film thickness increases the mean speed of the film, the system of hypothesis would be:

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

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

If we analyze the size for the samples both are less than 30 so for this case is better apply a t test to compare means, and the statistic is given by:

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

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine whether the means of two groups are equal to each other".

Calculate the statistic

We can replace in formula (1) the info given like this:

[tex]t=\frac{1.17-1.04}{\sqrt{\frac{0.11^2}{8}+\frac{0.09^2}{8}}}}=2.587[/tex]  

P-value

The first step is calculate the degrees of freedom, on this case:

[tex]df=n_{1}+n_{2}-2=8+8-2=14[/tex]

Since is a one sided test the p value would be:

[tex]p_v =P(t_{(14)}>2.587)=0.0108[/tex]

If we compare the p value and the significance level given [tex]\alpha=0.05[/tex] we see that [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, we have enough evidence to reject the null hypothesis on this case and the 25 mil film have a mean greater than the 20 mil film so then the claim is not appropiate

Answer:

30.5 in

Step-by-step explanation:

Answer:

30.5 inches

Step-by-step explanation:

Since the board is 77.47 cm and 1 inch is 2.54 cm you have to divide 77.47 by 2.54.

The average rate of change of the function g(x) over the interval from x = -8 to x = -4 is -2.

The average rate of change of a function over a certain interval is similar to finding the slope of the secant line that passes through the points on the graph of the function corresponding to the end points of the interval. In this case, for the function g(x) = x^2 + 10x + 23, we want to find the average rate of change over the interval from x = -8 to x = -4.

To do this, we calculate the change in g(x) divided by the change in x (\(\Delta x\)).

The value of the function at x = -8 is g(-8) = (-8)^2 + 10(-8) + 23 = 64 - 80 + 23 = 7.

The value of the function at x = -4 is g(-4) = (-4)^2 + 10(-4) + 23 = 16 - 40 + 23 = -1.

Now, the average rate of change is given by the formula:

Average rate of change = (g(-4) - g(-8)) / (-4 - (-8))

= (-1 - 7) / (-4 + 8) = -8 / 4 = -2

So, the average rate of change of the function g(x) over the interval from x = -8 to x = -4 is -2.

To increase the number of customers you talk to daily by 20%, you will need to calculate 20% of the current number of customers you talk to and add it to the original number.

To increase the number of customers you talk to daily by 20%, you will need to calculate 20% of the current number of customers you talk to daily and add it to the original number. In this case, you talk to an average of 8 customers per hour during an 8-hour shift, which means you talk to 8 x 8 = 64 customers per day. To increase this number by 20%, you need to calculate 20% of 64, which is 0.20 x 64 = 12.8. Round this number to the nearest whole number to get an increase of 13 customers. Finally, add this increase to the original number of customers to find the new number of customers you need to talk to per day: 64 + 13 = 77 customers per day.

Answer:

B is better option

Step-by-step explanation:

Answer:

B

Step-by-step explanation:

Answer:

a) Transition matrix:

[tex]\left[\begin{array}{ccc}0.90&0.10\\0.25&0.75\end{array}\right][/tex]

b) The long-term fraction of downtime of the computer is 0.286 or 28.6%.

c) The probability of being down 10 hours from now is independent of the inital state and is equal to 0.286.

Step-by-step explanation:

We have two states for the computer: Up and Down.

The rows will represent the actual state and the column the next state, and the numbers within the matrix will be the probabilities of transition from the state of the row to the state of the column.

- If the computer is Up, there is a probability of 0.9 of being Up in the next hour. Then, there is a probability of 0.1 of being Down in the next hour.

- If the computer is Down, there is a probability of 0.75 of being Down in the next hour. Then, there is a probability of 0.25 of being Up in the next hour.

a) The transition matrix becomes:

[tex]\left[\begin{array}{ccc}&U&D\\U&0.90&0.10\\D&0.25&0.75\end{array}\right][/tex]

b) We can consider that we have a long-term state (stable) [πU, πD] when the fraction of each state does not change. This can be expressed as:

[tex]\left[\begin{array}{ccc}\pi_U&\pi_D\end{array}\right] *\left[\begin{array}{ccc}0.90&0.10\\0.25&0.75\end{array}\right]=\left[\begin{array}{ccc}\pi_U&\pi_D\end{array}\right][/tex]

If we develop this multiplication of matrix we get:

[tex]0.90\pi_U+0.25\pi_D=\pi_U\\\\0.10\pi_U+0.75\pi_D=\pi_D[/tex]

As this equations are linear combinations of each other, we need another equation to solve this.

We also know that the sum of the fractions of uptime and downtime is equal to one.

Solving these equation, we can calculate the long-term downtime fraction:

[tex]0.90\pi_U+0.25\pi_D=\pi_U\\\\0.25\pi_D=(1-0.90)\pi_U=0.10\pi_U\\\\\pi_U=(0.25/0.10)\pi_D=2.5\pi_D\\\\\\\pi_D+\pi_U=1\\\\\pi_D+2.5\pi_D=1\\\\3.5\pi_D=1\\\\\pi_D=1/3.5=0.286[/tex]

The long-term fraction of downtime of the computer is 0.286 or 28.6%.

c) To know what is the probability that it will be down 10 hours from now if the computer is now on, we have to compute the transition matrix for 10 hours. This is:

[tex]T^{10}=\left( \left[\begin{array}{ccc}0.90&0.10\\0.25&0.75\end{array}\right]\right)^{10}= \left[\begin{array}{ccc}0.714&0.286\\0.714&0.286\end{array}\right][/tex]

This is considered a steady state already.

If the computer is up, the actual state is [1, 0].

If we multiply this by the transition matrix, we get:

[tex]\left[\begin{array}{ccc}1&0\end{array}\right] *\left[\begin{array}{ccc}0.714&0.286\\0.714&0.286\end{array}\right]=\left[\begin{array}{ccc}0.714&0.286\end{array}\right][/tex]

The probability of being down 10 hours from now is independent of the inital state and is equal to 0.286.

Answer:

Check below for the required explanations

Step-by-step explanation:

The population correction factor is given by the formula :

PCF = [(N-n)/(N-1)]^1/2..........(1)

a) When the sample size is smaller than 5% of N. That is n < 0.05N

If n = 0.05N is substituted into the PCF formula, PCF will be approximately 1.

For a value of 1, PCF can be safely ignored.

b) N = 200

i) n = 10% N

n = 0.1 × 200 = 20

Substitute n = 20 into equation (1)

PCF = (200-20)/(200-1)]^1/2

PCF = 0.95

ii) n = 5% N

n = 0.05× 200 = 10

Substitute n = 20 into equation (1)

PCF = (200-10)/(200-1)]^1/2

PCF = 0.98

iii) i) n = 3% N

n = 0.03 × 200 = 6

Substitute n = 20 into equation (1)

PCF = (200-6)/(200-1)]^1/2

PCF = 0.99

iiii) n = 1% N

n = 0.01 × 200 = 2

Substitute n = 20 into equation (1)

PCF = (200-2)/(200-1)]^1/2

PCF = 0.998(approx. =1)

It is noticed that the smaller the sample size, the closer the population correction factor to unity. At 1% of the population, the population correction factor is negligible

The question deals with the mechanism of reactions between ketones and amines, acid-base reactions, and alkylation reactions. The primary step of a ketone-amine reaction involves the nitrogen attacking the carbonyl carbon to eventually form an imine or enamine. The acid-base reaction between acetic acid and ammonia results in the ammonium and acetate ions.

The student's question is about organic reaction mechanisms, specifically the reactions between ketones and amines, and other related reactions such as acid-base reactions between acetic acid and ammonia. In the case of a ketone reacting with a primary or secondary amine, the first step typically involves nucleophilic attack by the nitrogen of the amine on the electrophilic carbonyl carbon of the ketone. This produces a tetrahedral intermediate which, after losing a water molecule, forms an imine or an enamine depending on whether a primary or secondary amine was used respectively.

For the acid-base reaction between acetic acid (CH3CO2H) and ammonia (NH3), the mechanism begins with the lone pair on the nitrogen of ammonia attacking the hydrogen of acetic acid. This is shown with a curved arrow from the nitrogen to the hydrogen. This results in the formation of the ammonium ion (NH4+) and the acetate ion (CH3CO2-).

The alkylation reaction at the alpha-carbon of a ketone or aldehyde and the concept of kinetic versus thermodynamic control are also touched upon. In an alkylation reaction, the first step usually involves the generation of an enolate ion from the ketone or aldehyde, followed by its nucleophilic attack on an alkyl halide.

Answer:

(C) No, the probability of making a second purchase is not equal to the probability of making a second purchase given that a coupon was sent.

Step-by-step explanation:

Let A = the customer makes a second purchase within 30 days and let B = customer is sent a coupon. Events A and B are independent if P(A) = P(A | B).

P(A) = P(the customer makes a second purchase within 30 days) = \frac{50}{100} = 0.5  

100

50

​  =0.5

P(A | B) = P(the customer makes a second purchase within 30 days | customer is sent a coupon) = \frac{34}{60} = 0.567  

60

34

​  =0.567

Because P(A) ≠ P(A | B) making a second purchase is not independent of being sent a coupon.

Answer:

87 green apples

Step-by-step explanation:

Red apples  : green apples = 2 : 3

Number of red apples = 2x

Number of green apples = 3x

Total apples = 145

3x + 2x = 145

5x = 145

x = 145/5

x = 29

Number of green apples = 3x = 3 * 29 = 87

Answer:

~20 oz

Step-by-step explanation:

Originally, Bo had 32 ounces of flour, which is around 30 ounces. Then, he added in 47 ounces, which is about 50. So, now the new total is about 30 + 50 = 80 ounces.

During the week, he used up some of those ~80 ounces of flour. He used up enough so that at the end of the week, there was only 61 ounces, or approximately 60 oz, left. The difference between these two numbers must be how much Bo used:

80 - 60 = 20 ounces

Thus, the answer is about 20 ounces.

Hope this helps!

Bo started with 79 ounces of flour (32 ounces original and 47 ounces added), and ended with 61 ounces remaining, so he used an estimated 18 ounces of flour during the week.

To determine how much flour Bo used during the week, we need to find out how much the total weight of flour was at the beginning of the week, and then subtract the weight of the flour that was left at the end of the week.

At first, Bo's container had 32 ounces of flour. On Monday, he added 47 more ounces. Therefore, the weight of the flour at the beginning of the week was 32 + 47 = 79 ounces.

At the end of the week, the leftover flour weighed 61 ounces. So, to estimate how much flour Bo used, we subtract the leftover weight from the original total weight: 79 ounces - 61 ounces = 18 ounces.

So, Bo used an estimated 18 ounces of flour during the week.

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3/ 4+2/ 5=1 3/ 20

3 forths + 2 fifths = 1 and 3 twentyiths

Hope i helped! :)

Answer:

.25 or 1/4

Step-by-step explanation:

1/3-1/12 is .25 or if you turn it into a fraction it is 1/4.Because one quarter out of a dollar equals .25 cents.

(a) Null Hypothesis (H0): μ ≤ 100 ppb (The average level of BPA in the tomato soup is less than or equal to 100 ppb)

Alternative Hypothesis (H1): μ > 100 ppb (The average level of BPA in the tomato soup is greater than 100 ppb)

(b) A Type I Error would occur if the agency finds evidence that the average level of BPA is greater than 100 ppb (rejects H0) when, in fact, the true average level is less than or equal to 100 ppb.

(c) A Type II Error would occur if the agency fails to find evidence that the average level of BPA is greater than 100 ppb (fails to reject H0) when, in fact, the true average level is greater

(a) Null Hypothesis (H₀): The average level of BPA in the company's tomato soup is less than or equal to 100 ppb.

Mathematically: μ ≤ 100 ppb

Alternative Hypothesis (H₁):

The average level of BPA in the company's tomato soup is greater than 100 ppb.

Mathematically: μ > 100 ppb

(b) A Type I error occurs when we reject the null hypothesis when it is actually true. In this context, a Type I error would mean that the consumer protection agency concludes that the average BPA level is greater than 100 ppb and recalls the soup and sues the company, when in reality, the average BPA level is less than or equal to 100 ppb. This would result in unnecessary product recall and legal action against the company.  

(c) A Type II error occurs when we fail to reject the null hypothesis when it is actually false. In this context, a Type II error would mean that the consumer protection agency concludes that the average BPA level is less than or equal to 100 ppb and does not recall the soup or sue the company, when in reality, the average BPA level is greater than 100 ppb. This would allow unsafe products to remain on the market, potentially harming consumers.  

Answer:

x = theta = 0°

Step-by-step explanation:

Given the trigonometry function

Tan²x/2-2 cos x = 1

Tan²x-4cosx = 2 ... 1

From trigonometry identity

Sec²x = tan²x+1

tan²x = sec²x-1 ... 2

Substituting 2 into 1, we have:

sec²x-1 -4cosx = 2

Note that secx = 1/cosx

1/cos²x - 1 - 4cosx = 2

Let cosx. = P

1/P² - 1 - 4P = 2

1-P²-4P³ = 2P²

4P³+2P²+P²-1 = 0

4P³+3P² = 1

P²(4P+3) = 1

P² = 1 and 4P+3 = 1

P = ±1 and P = -3/4

Since cosx = P

If P = 1

Cosx = 1

x = arccos1

x = 0°

If x = -1

cosx = -1

x = arccos(-1)

x = 180°

Since our angle must be between 0 and 1 therefore x = 0°

Answer:

89.44% probability that the total weight of the King Salmons caught is greater than 575 lbs

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For sums of size n from a population, the mean is [tex]\mu*n[/tex] and the standard deviation is [tex]\sigma\sqrt{n}[/tex]

The weight of the King Salmons are i.i.d. ∼ Normal with µK = 150 lbs and σK = 10 lbs. 4 king salmons.

So [tex]\mu = 4*150 = 600, \sigma = 10\sqrt{4} = 20[/tex]

What is the probability that the total weight of the King Salmons caught is greater than 575 lbs?

This is 1 subtracted by the pvalue of Z when X = 575. So

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]Z = \frac{575 - 600}{20}[/tex]

[tex]Z = -1.25[/tex]

[tex]Z = -1.25[/tex] has a pvalue of 0.1056

1 - 0.1056 = 0.8944

89.44% probability that the total weight of the King Salmons caught is greater than 575 lbs

Answer:

For this case we have the following info related to the time to prepare a return

[tex] \mu =90 , \sigma =14[/tex]

And we select a sample size =49>30 and we are interested in determine the standard deviation for the sample mean. From the central limit theorem we know that the distribution for the sample mean [tex]\bar X[/tex] is given by:

[tex]\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})[/tex]

And the standard deviation would be:

[tex]\sigma_{\bar X} =\frac{14}{\sqrt{49}}= 2[/tex]

And the best answer would be

b. 2 minutes

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Solution to the problem

For this case we have the following info related to the time to prepare a return

[tex] \mu =90 , \sigma =14[/tex]

And we select a sample size =49>30 and we are interested in determine the standard deviation for the sample mean. From the central limit theorem we know that the distribution for the sample mean [tex]\bar X[/tex] is given by:

[tex]\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})[/tex]

And the standard deviation would be:

[tex]\sigma_{\bar X} =\frac{14}{\sqrt{49}}= 2[/tex]

And the best answer would be

b. 2 minutes

Answer: The top of the ladder is moving towards the floor at a rate of 0.75 ft/sec

Step-by-step explanation: Please see the attachments below

Answer:

Timmy is 18 and Tommy is 5.

Step-by-step explanation:

Step-by-step explanation:

So you have to find out tha ages which add up to 23 so if Tommy is 9 years old and when we add 5

So Timmy age = 9 + 5 = 14

Now if we add 14 and 9 the answer is 23

It means Timmy is 14 years old and Tommy is 9 years old

Answer and Step-by-step explanation:

We can easily add up these two numbers:

    1,563,001

+     253,965

___________

    1,816,966

Now, we need to write out the answer is words:

"One million, eight hundred sixteen thousand, nine hundred and sixty-six"

Hope this helps!

Answer:

Step-by-step explanation:

1,563,001

+ 253,965

___________

1,816,966

In words:

"One million Eight Hundred Sixteen Thousan Nine hundred and. Sixty Six"

Answer:

Step-by-step explanation:

Given Parameters

Mean, [tex]x[/tex] = 180

total samples, n = 20

Standard dev, [tex]\sigma[/tex] = 30

[tex]\alpha[/tex] = 1 - 0.95 = 0.05 at 95% confidence level

Df = n - 1 = 20 - 1 = 19

Critical Value, [tex]t_\alpha[/tex], is given by

[tex]t_{c}=t_{\alpha, df} = t_{0.05,19} = 1.729[/tex]

a).

Confidence Interval, [tex]\mu[/tex], is given by the formula

[tex]\mu = x +/- t_c \times \frac{s}{\sqrt{n} }[/tex]

[tex]\mu = 180 +/- 1.729 \times \frac{30}{\sqrt{20} }[/tex]

[tex]\mu = 180 +/-11.5985[/tex]

[tex]191.5985 > \mu > 168.4015[/tex]

b).

Critical Value, [tex]t_{\alpha/2}[/tex], is given by

[tex]t_{c}=t_{\alpha/2, df} = t_{0.05/2,19} = 2.093[/tex]

Confidence Interval, [tex]\mu[/tex], is given by

[tex]\mu = x +/- t_c \times \frac{s}{\sqrt{n} }[/tex]

[tex]\mu = 180 +/- 2.093 \times \frac{30}{\sqrt{20} }[/tex]

    = 180 +/- 14.0403

    = 165.9597 < [tex]\mu[/tex] < 194.0403

Options:

a. His predicted weight loss was 5.5 pounds higher than his actual weight loss.

b. His actual weight loss was 5.5 pounds higher than his predicted weight loss.

c. His actual weight loss was 5.5 pounds higher than it would have been if he didn’t exercise.

d. His predicted weight loss was 5.5 pounds higher than it would have been if he didn’t exercise.

Answer:

Option B. His actual weight loss was 5.5 pounds higher than his predicted weight loss.

Step-by-step explanation:

In regression analysis, the difference between the observed value of the dependent variable (y) and the predicted value (ŷ) is called the residual (e). Residual value= Observed value - Predicted value.i.e. e = y - ŷ

Since the residual weight of the client was 5.5 pounds, this means that His actual weight after compliance with the exercise program his 5.5 pounds higher than what he predicted.

Final answer:

The client's residual of 5.5 pounds means they lost 5.5 pounds more than predicted by the exercise program's linear regression model, indicating a discrepancy between the predicted and actual weight loss.

Explanation:

When a client has been told that his residual was 5.5 pounds in the context of a linear regression, it refers to the difference between the actual weight the client lost and the weight the regression model predicted they would lose based on their percent compliance with the exercise program. A residual of 5.5 pounds indicates that the client lost 5.5 pounds more than what the model predicted. Residuals are used to measure the accuracy of regression models; if they are small, it suggests that the model is accurately predicting outcomes. However, large or systematic residuals can indicate a problem with the model's fit to the data.

Answer:

i am positive he can

Step-by-step explanation:

sorry if this is wrong...also can i pls have brainliest

Answer:

Answer is 32 if you are doing DeltaMath

Step-by-step explanation:

Answer:

1.372 × 10^3

Step-by-step explanation:

Translation from Google

the area of ​​a rectangle measures 15 square units. if one side of a rectangle is 3.75 units long how much unit is the perimeter of the rectangle?

Answer:

15.5 unidades

Step-by-step explanation:

Area of rectangle is given by the product of its length and width and expressed as

A=lw

Where l is length, w is width and A is area.

Similarly, perimeter is given by

P=2(l+w)

Given that A=15 and w=3.75

15=3.75l

l=15÷3.75=4 unidades

Now perimeter will be

P=2(4+3.75)=2(7.75)=15.5 units

Answer:

Ounces is smaller than lbs

Step-by-step explanation:

16 ounces = 1 lbs

Ounces is smaller than lbs

Answer:

An ounce is the smallest unit for measuring weight, a pound is a larger unit, and a ton is the largest unit

Step-by-step explanation:

Please give me brainliest

Answer:

3.10h + 2.30b ≥ 100

Step-by-step explanation:

Tammy earns $3.10 for each hour,

Let h represents hour,

So total earning for h number of hours will be 3.10h

Tammy earns $2.30 for each bushel of apples

Let b represents bushel of apples,

So total earning for b number of bushels will be 2.30b

Tammy's goal is to earn at least $100 this week

Therefore, to reach her goal the inequality will be

3.10h + 2.30b ≥ 100

Where h is the number of hour and b is the number of bushels.