Suppose Frances is a researcher at Beaded Gemsz, a company that makes beaded jewelry. She wants to evaluate whether using better equipment during the current year has increased jewelry-making productivity. The company's reporting team estimated an average daily production yield of 105 units per store from previous years. Frances conducts a one-sample z - test with a significance level of 0.08 , acquiring daily unit yield data from each of the stores' databases for 45 randomly selected days of the year. She obtains a P -value of 0.06 . The power of the test to detect a production increase of 12 units or more is 0.85 . What is the probability that Frances concludes that the new equipment increases the average daily jewelry production when in fact the new equipment has no effect

Answer:

sample proportion is 0.75

Step-by-step explanation:

given data

confidence = 95%

Pinellas County  between = 0.73 and 0.77

solution

We write confidence interval in terms of p and E as

(p - E ) <  P  <  ( p + E )     ................1

when we compare it 0.73 < p < 0.77

we get        

so here

p - E = 0.73    ................2

and E is 0.02 so

p - 0.02 = 0.73

p = 0.75

The sample proportion of on-line SPC students who live in Pinellas County is 0.75.

The sample proportion is the point estimate that lies in the middle of the confidence interval.
To find the sample proportion from the given confidence interval, you calculate the average of the lower and upper bounds.

The lower bound is 0.73, and the upper bound is 0.77.
0.73 + 0.77 = 1.50
1.50 / 2
= 0.75

Therefore, the sample proportion of on-line SPC students who live in Pinellas County is 0.75.

Answer:

associative property of addition

Step-by-step explanation:

The 5 is substituted into the parentheses and the 7 is taken out.

Answer:

14.5

step by step explanation:

1450÷100= 14.5

Final answer:

Mrs. Ada paid #14.50 for each egg after being charged #1450 for 100 eggs. This is calculated by dividing the total cost by the number of eggs.

Explanation:

To calculate the cost of each egg when Mrs. Ada charged #1450 for 100 eggs, we need to divide the total cost by the number of eggs. This is a simple division problem under the subject of mathematics.

The formula to find the cost per egg is:

Total cost of eggs ÷ Number of eggs = Cost per egg

#1450 ÷ 100 eggs = #14.50 per egg

Therefore, Mrs. Ada paid #14.50 for each egg.

Answer:

C) y=4x-12.5

Step-by-step explanation:

8x-2y=25

-2y=25-8x

y=-12.5+4x

y=4x-12.5

Therefore C is the right answer

Answer: the answer is 14

Step-by-step explanation:

Answer:

14

Step-by-step explanation:

Correct on edge 2021

Answer:

P(green or purple​) = 0.576

Step-by-step explanation:

A probability is the number of desired outcomes divided by the number of total outcomes.

In this problem, we have that:

32 + 47 + 21 + 25 = 125 blocks.

Of those, 47 + 25 = 72 are green of purple

​P(green or purple​) = 72/125 = 0.576

Answer: two estimates of the variance are relatively close together

Step-by-step explanation:

Answer:

[tex]438.53-2.12\frac{14.988}{\sqrt{17}}=430.82[/tex]    

[tex]438.53+2.12\frac{14.988}{\sqrt{17}}=446.24[/tex]    

So on this case the 95% confidence interval would be given by (430.82;446.24)    

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

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".

[tex]\bar X[/tex] represent the sample mean for the sample  

[tex]\mu[/tex] population mean (variable of interest)

s represent the sample standard deviation

n represent the sample size  

Solution to the problem

The confidence interval for the mean is given by the following formula:

[tex]\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]   (1)

In order to calculate the mean and the sample deviation we can use the following formulas:  

[tex]\bar X= \sum_{i=1}^n \frac{x_i}{n}[/tex] (2)  

[tex]s=\sqrt{\frac{\sum_{i=1}^n (x_i-\bar X)}{n-1}}[/tex] (3)  

The mean calculated for this case is [tex]\bar X=438.53[/tex]

The sample deviation calculated [tex]s=14.988[/tex]

In order to calculate the critical value [tex]t_{\alpha/2}[/tex] we need to find first the degrees of freedom, given by:

[tex]df=n-1=17-1=16[/tex]

Since the Confidence is 0.95 or 95%, the value of [tex]\alpha=0.05[/tex] and [tex]\alpha/2 =0.025[/tex], and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.025,16)".And we see that [tex]t_{\alpha/2}=2.12[/tex]

Now we have everything in order to replace into formula (1):

[tex]438.53-2.12\frac{14.988}{\sqrt{17}}=430.82[/tex]    

[tex]438.53+2.12\frac{14.988}{\sqrt{17}}=446.24[/tex]    

So on this case the 95% confidence interval would be given by (430.82;446.24)    

Answer:

Amount of water = x³- 4/3 π (x/2)³

Step-by-step explanation:

Let's assume there is a cubic tank, we have 512 spheres in it. Now we have to write an expression in terms of pie.

Let's suppose:

x = edge of the tank

volume of a cube = x³

volume of sphere = 4/3 π r³

where, r = radius of a sphere.

So, we have 512 spheres in total, it means there are 8 spheres in a single row.

(8)³ = 512

It means radius of a single sphere will be = x/16, where x represents the edge of the cubic tank.

Radius of sphere = x/16

So, the formula to calculate the amount of water in the tank will be:

Amount of water in the tank = Volume of cube - Volume of all spheres.

Amount of water = x³ - 512 x ( 4/3 π r³)

Amount of water = x³- 512 x ( 4/3 π (x/16)³)

Amount of water = x³- 512 x ( 4/3 π x³/4096)

Amount of water =  x³- 4/3 π x³/8

Amount of water = x³- 4/3 π (x/2)³

Hence, this will be the expression required.

Answer:

Step-by-step explanation:

Given that,

The square based prism has  dimensions is

6 by 6 by 10

Length = 6

Width = 6

Height = 10

Slant height of pyramid is given as

h = 10.6

Note: The base of the pyramid matches the top of the square prism, so it's square-based prism.

So, we are going to have

4 rectangular faces(i.e the square Base prism rectangular faces)

1 square face ( the based of the prism)

four triangular faces( the top pyramid)

So, area of the four face

It is a rectangular shape and it is calculated using

A = length × Breadth

Area of one face is

A = L × W

A = 6 × 10 = 60 Square units

And there are 4 similar rectangle

So, area of the four rectangles is

A' = 4 × 60 = 240 square unit

Now, area of the square base below can be calculated using

A = s²

A" = L² = 6² = 36 Square units

Now, area of the four triangle pyramid at the top

Area of triangle is given as

A = ½bh

A = ½ × 6 × 10.6

A = 31.8 square units.

The area of the four triangles becomes

A"' = 4 × 31.8

A"' = 126 square units

Then, the total area of the shape is

A(total ) = A' + A" + A"'

A(total) = 240 + 36 + 126

A(total) = 402 Square units

So, the total area of the solid shape is 402 Square units

Answer:

a)The number of aces in the poker hand is greater

b)It is about[tex]\sqrt{2}[/tex] as accurate.

Answer:

do you know your radius or diameter?

Answer:

see explaination

Step-by-step explanation:

Let mu1 be the mean for exclusively breaststroke

Let mu2 be the mean for individual medley

----------------------------------------------------------------------------------------------------------

(a) H o: mu1=mu2 (i.e. null hypothesis)

Ha: mu1> mu2 (i.e. alternative hypothesis)

----------------------------------------------------------------------------------------------------------

(b) Since both sample sizes are grearter than n=30, we can use normal distriubtion.

It is a one-tailed test.

Given a=0.01, the critical value is Z(0.01) =2.33 (from standard normal table)

So the rejection region is Z>2.33

----------------------------------------------------------------------------------------------------------

(c) The test statistic is

Z=(xbar2-xbar2)/sqrt(s1^2/n1+s2^2/n2)

=(9017-5853)/sqrt(7162^2/130+1961^2/80)

=4.76

----------------------------------------------------------------------------------------------------------

(d) Since Z=4.76 is larger than 2.33, we reject the null hypothesis.

----------------------------------------------------------------------------------------------------------

(e) In conclusion there is sufficient evidence to indicate that the average number of meter per week spent practicing breaststroke is greater for exclusive breaststrokers than it is for those swimming individual medley

There is sufficient evidence to indicate that the mean number of breaststroke is greater for exclusive breaststrokers than for swimming individual medley.

In null hypotheses, there is no relationship between the two phenomena under the assumption that it is not associated with the group. And in alternative hypotheses, there is a relationship between the two chosen unknowns.

Let μ₁ be the mean for the exclusive breaststroke.

Let μ₂ be the mean for the individual medley.

For the null hypothesis, we have

H₀: μ₁ = μ₂

For the alternative hypothesis, we have

Hₐ: μ₁ > μ₂

The sample size of both is greater than 30, then the normal distribution will be

a = 0.01

The critical value is z(0.01) = 2.33 (From standard normal table)

So the rejection region is z > 2.33

The test statistic will be

[tex]z = \dfrac{\mu_2 - \mu_1}{\sqrt{s^2_1/n_1 + s^2_2/n_2}}\\\\\\z = \dfrac{9017 - 5853}{\sqrt{7162^2/130+1961^2/80}}\\\\\\z = 4.76[/tex]

Since the value of z is greater than 2.33, then we reject the null hypothesis.

More about the null hypotheses and alternative hypotheses link is given below.

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Answer: The coordinates of point be are (1,-1)

Step-by-step explanation:

The reflected point will be equidistant from the point over which it is reflected as the original point and in the same line as the original point and the reflected point.

Find the difference between the x and y values of the given points and add that value (distance) to the reflection point.

x-values: 4-7 = -3   y-values: 0-1 = -1

Add to reflection point  x: 4-3 = 1     y: 0 -1 = -1

Final answer:

To reflect point A(7, 1) over point (4, 0) to find point B, calculate the horizontal and vertical distances from A to (4, 0) and subtract these distances from (4, 0) to get B's coordinates, resulting in point B being at (1, -1).

Explanation:

To find the coordinates of point B after reflecting point A(7, 1) over point (4, 0), we need to apply the concept of reflections in the Cartesian plane. When a point is reflected over another, the line joining the original point and the point of reflection is bisected perpendicularly by the point of reflection. This means that point B will have the same distance from (4, 0) as point A, but in the opposite direction.

Here's the step-by-step method to find the coordinates of B:

Calculate the horizontal and vertical distances from A to the mirror point (4, 0): Horizontal distance = 7 - 4 = 3, Vertical distance = 1 - 0 = 1.

Subtract these distances from the mirror point to find B's coordinates: B's x-coordinate = 4 - 3 = 1, B's y-coordinate = 0 - 1 = -1.

So, the coordinates of point B after the reflection are (1, -1).

Answer:

The probability that the proportion of freshmen in the sample of 90 who plan to major in a STEM discipline is between 0.29 and 0.37 is P=0.0166.

Step-by-step explanation:

The question is incomplete. You have to add:

Find the probability that the proportion of freshmen in the sample of 90 who plan to major in a STEM discipline is between 0.29 and 0.37.

We have a sample of n=90 out of a population with a proportion p=0.28.

We have to calculate the probability that the sample has a proportion between 0.29 and 0.37.

First, we calculate the standard deviation of the sampling distribution:

[tex]\sigma_M=\dfrac{\sigma}{\sqrt{n}}=\sqrt{\dfrac{p(1-p)}{n}}=\sqrt{\dfrac{0.28*0.72}{90}}=\sqrt{0.0024}=0.047[/tex]

We can now calculate the z-score for 0.29 and 0.37

[tex]z_1=\dfrac{p_1-p}{\sigma}=\dfrac{0.29-0.28}{0.0047}=\dfrac{0.01}{0.0047}=2.13\\\\\\z_2=\dfrac{p_2-p}{\sigma}=\dfrac{0.37-0.28}{0.0047}=\dfrac{0.09}{0.0047}=19.15[/tex]

Now, we can calculate the probability as:

[tex]P(0.29<\hat p<0.37)=P(2.13<z<19.15)=P(z<19.15)-P(z<2.13)\\\\P(0.29<\hat p<0.37)=1-0.9834=0.0166[/tex]

The situation is describing a binomial probability scenario. Given the probability of a freshman choosing a STEM discipline as 28% (0.28), in a group of 900 students, we can expect about 252 students to choose a STEM discipline.

The reported statistic suggests that 28% of freshmen entering college in a recent year planned to major in a STEM discipline. Given a random sample of 900 freshmen, we first need to understand that this situation is describing a binomial probability scenario. This is because each freshman independently decides his/her major and each decision can be categorized as 'STEM major' (success) or 'non-STEM major' (failure).

1. The probability of success (p) = 0.28.

2. The size of the collection of individuals (n) = 900.

Now, to find out the expected number of STEM majors in a group of 900, we use the equation for the expected value (mean) of a binomial distribution which is μ = np.

Substitute: μ = (900)(0.28) = 252. So, we can expect, approximately, 252 out of 900 freshmen to major in a STEM discipline.

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Answer: here are 48 adults of this younger age group.

Step-by-step explanation:

Since we have given that

Error = 0.10

p = 23% = 0.23

At 90% level of significance, i.e. α = 0.10

So, the value of z = 1.645

[tex]n=(\dfrac{z}{E})^2p(1-p)\\\\n=(\dfrac{1.645}{0.1})^2(0.23)(1-0.23)\\\\n=270.6025\times 0.23\times 0.77\\\\n=47.92\\\\n\approx 48[/tex]

Hence, there are 48 adults of this younger age group.

Answer:

one hundred which is 100

Final answer:

To calculate a 95% confidence interval for the mean (μ) of a laboratory scale's measurements, the sample mean, standard deviation, and t-distribution are utilized to find the interval, which is approximately 0.9444 to 1.0356 grams. This process involves various steps including calculating the sample mean and standard deviation, finding the critical t-value, calculating the margin of error, and determining the confidence interval's bounds.

Explanation:

To compute a 95% confidence interval for μ, the mean of the weighings when the true weight is 1 gram, we first calculate the sample mean (μ) and the standard deviation (s) of the given measurements. The measurements are: 0.95, 1.02, 1.01, and 0.98 grams. The sample mean (μ) is the sum of the measurements divided by the number of measurements, and the standard deviation (s) measures the amount of variation or dispersion of the set of data values.

Calculate the sample mean (μ): (μ) = (0.95 + 1.02 + 1.01 + 0.98) / 4 = 0.99 grams.

Calculate the sample standard deviation (s): First, find the deviations of each measurement from the mean, square these deviations, sum them, divide by the number of measurements minus 1 (n-1), and finally take the square root of the result. (s) ≈ 0.02887 grams.

Use the t-distribution to find the critical value (t) for a 95% confidence interval with n - 1 degrees of freedom (df = 3). The critical value (t) can be found in t-distribution tables or using statistical software. For df = 3 and a 95% confidence level, (t) ≈ 3.182.

Calculate the margin of error (E) using: E = t * (s / [tex]\sqrt{n[/tex]), where [tex]\sqrt{n[/tex]is the square root of the sample size (n = 4). E ≈ 3.182 * (0.02887 / [tex]\sqrt{4[/tex] ) ≈ 0.0456 grams.

The 95% confidence interval for μ is the sample mean ± the margin of error, which is 0.99 ± 0.0456 grams, or approximately 0.9444 to 1.0356 grams.

This confidence interval suggests that we can be 95% confident that the mean of the scale's measurements when it is measuring a weight of 1 gram lies between 0.9444 grams and 1.0356 grams.

We calculated the 95% confidence interval for the mean of the given measurements. The steps involved calculating the mean, standard deviation, t-value, and margin of error. The confidence interval is 0.9397 g to 1.0403 g.

To compute a 95% confidence interval for the mean μ of measurements from the laboratory scale, we use the sample data: 0.95 g, 1.02 g, 1.01 g, and 0.98 g. We need to follow these steps:

[tex]\bar_x[/tex] = (0.95 + 1.02 + 1.01 + 0.98) / 4

= 0.99 g

s = [tex]\sqrt{\frac{{(0.95 - 0.99)^2 + (1.02 - 0.99)^2 + (1.01 - 0.99)^2 + (0.98 - 0.99)^2}}{{4 - 1}}}[/tex]

≈ 0.0316 g

Find the critical t-value for 3 degrees of freedom (df = n - 1 = 4 - 1 = 3) at the 95% confidence level.

This value is roughly t0.025,3 ≈ 3.182.

ME = t0.025,3 * [tex](s / \sqrt{n})[/tex]

≈ 3.182 * (0.0316 / 2)

≈ 0.0503 g

([tex]\bar_x[/tex] - ME) to  ([tex]\bar_x[/tex] + ME) = (0.99 - 0.0503) to (0.99 + 0.0503)

= 0.9397 g to 1.0403 g

Therefore, the 95% confidence interval for the mean mass μ of the standard weight is 0.9397 g to 1.0403 g.

Answer:

With garlic​ treatment, the mean change in LDL cholesterol is not greater than 0.

Step-by-step explanation:

The dependent t-test (also known as the paired t-test or paired samples t-test) compares the two means associated groups to conclude if there is a statistically significant difference amid these two means.

In this case a paired t-test is used to determine the effectiveness of garlic for lowering​ cholesterol.

A random sample of 81 subjects were treated with raw garlic. Cholesterol levels were measured before and after the treatment.

The hypothesis for the test can be defined as follows:

H₀: With garlic​ treatment, the mean change in LDL cholesterol is not greater than 0, i.e. d ≤ 0.

Hₐ: With garlic​ treatment, the mean change in LDL cholesterol is greater than 0, i.e. d > 0.

The information provided is:

[tex]\bar d=0.40\\SD_{d}=16.2\\\alpha =0.01[/tex]

Compute the test statistic value as follows:

[tex]t=\frac{\bar d}{SD_{d}/\sqrt{n}}\\\\=\frac{0.40}{16.2/\sqrt{81}}\\\\=0.22[/tex]

The test statistic value is 0.22.

Decision rule:

If the p-value of the test is less than the significance level then the null hypothesis will be rejected and vice-versa.

Compute the p-value of the test as follows:

[tex]p-value=P(t_{n-1}>0.22)\\=P(t_{80}>0.22)\\=0.4132[/tex]

*Use a t-table.

The p-value of the test is 0.4132.

p-value= 0.4132 > α = 0.01

The null hypothesis was failed to be rejected.

Thus, it can be concluded that with garlic​ treatment, the mean change in LDL cholesterol is not greater than 0.

Answer:

x=0

Step-by-step explanation:

Cancel -8 on both sides.

3x=−x

Subtract -x from both sides.

3x+x=0

Simplify  3x+x  to 4x.

4x=0

Divide both sides by 4

x=0

Brainliest please!

Answer:

Step-by-step explanation:

0

Answer:

all the households in given state. part 2 is 1565 households surveyed.

Step-by-step explanation:

Part 1

A. all the households given state

Part 2

B. 1565 households surveyed.

Answer:

679

Step-by-step explanation:

The goal of this exercise is to find a three digit number given five statements.

1 - We can conclude that two digits out of 964 are correct but in the wrong place.

2 -  One digit out of 147 is correct, but in the wrong place

3 - One digit out of 189 is correct and in the right place. Since 1 is on the same place in 147 and 189, 1 is not the correct digit. The correct digit is either 8 or 9.

4 -   One digit out of 286 is correct, but in the wrong place. Since 8 is on the same place in 189 and 286, 8 is not the correct digit. We can then conclude that 9 is correct (statement 3) and in the right place (third) and that either 2 or 6 are correct but in the wrong place.

5 -  523 are all wrong. We can then conclude that 6 is correct and that is not in the third or second place, which leaves it in the first place.

If 1 and 4 are incorrect, from the second statement, we infer that 7 is the remaining correct digit at the second place.

Therefore the number is 679

Answer:

C.

Step-by-step explanation:

Answer:

Step-by-step explanation:

Hello!

The manager of the store made a linear regression analysis to study if the amount of newspaper advertising (independent variable, X) significantly affects the sales (dependent variable, Y)

The coefficient of determination R² is a statistic that measures the percentage of the variability of Y that is explained by X in the context of the regression model. It also determines the ability of the model to replicate the results of the analysis.

The Excel output is attached below, the calculated determination coefficient is:

R²= 0.726

Interpretation

72.6% of the variability of the estimated average daily sales of the grocery store is explained by the amount of newspaper advertisement placed under the estimated model.

I hope this helps!

Answer:

Year Prediction Actual

2002 12,500 8,342

2004 16,250 10,783

2006 21,250 12,463

2008 26,250 8,776

2010 32,500 11,578

Step-by-step explanation:

look at the graph and look for where the year and average meet fir each year. then look up online  the actual closing price.

Without specific input data and a graph, it is not possible to perform this task here. However, typically, one would estimate values from the graph for specified years and then compare with the actual DJIA values researched online.

This task requires estimations based on an exponential function graph for the Dow Jones Industrial Average (DJIA) for specified years and then comparing these estimations with the actual values. However, without the graph and data, this is not possible to demonstrate here specifically.

Usually, to estimate the values from the graph from years 2002, 2004, 2006, 2008, and 2010, we would look at the y-axis (representing DJIA's value) for the corresponding years on the x-axis. The estimated values can then be compared with the actual yearly performance of DJIA, which can be researched online on credible financial platforms.

It's worth noting that this task combines mathematical skills and research ability, employing both to draw a comparison between actual and predicted results from a mathematical model.

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Answer:

a) The decision rule is:

Reject the null hypothesis if P-value is under 0.05 (or the test statistic is larger than z=-1.645).

b) Test statistic z=-0.30

c) The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that there has been a significant decrease in the proportion of students who change their major after the first year in this program.

Step-by-step explanation:

This is a hypothesis test for a proportion.

The claim we have to test is that there has been a significant decrease in the proportion of students who change their major after the first year in this program.

Then, the null and alternative hypothesis are:

[tex]H_0: \pi=0.5\\\\H_a:\pi< 0.5[/tex]

The significance level is α=0.05.

The sample has a size n=100.

The sample proportion is p=0.48.

[tex]p=X/n=48/100=0.48[/tex]

The standard error of the proportion is:

[tex]\sigma_p=\sqrt{\dfrac{\pi(1-\pi)}{n}}=\sqrt{\dfrac{0.5*0.5}{100}}\\\\\\ \sigma_p=\sqrt{0.0025}=0.05[/tex]

We can calculate the test statistic as:

[tex]z=\dfrac{p-\pi-0.5/n}{\sigma_p}=\dfrac{0.48-0.5+0.5/100}{0.05}=\dfrac{-0.015}{0.05}=-0.3[/tex]

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

[tex]P-value=P(z<-0.3)=0.3821[/tex]

The P-value (0.3821) is bigger than the significance level (0.05), then the effect is not significant.

The null hypothesis failed to be rejected.

If we use the critical value approach, the critical value of z for this test with 5% significance level is z=1.645.

There is not enough evidence to support the claim that there has been a significant decrease in the proportion of students who change their major after the first year in this program.

Answer:

d. parabola, 0°

Step-by-step explanation:

y² + 8x - 0

y² = -8x

Where x = cos t  ,  y = sin t

Sin² t = -8 Cos t

1 - Cos² t = -8 Cos t

- Cos² t + 8 Cos t + 1 = 0

t = 2лπ ± (3 + √10) , л∈Z

Angle of rotation

The correct options, given the base dimensions and assuming a height of 6 inches, would be 2 and 4, while options 1, 3, 5, and 6 cannot be confirmed without more information.

When analyzing the cross sections of a rectangular prism, it is crucial to consider the orientation of the cut in relation to the base and sides of the prism. The correct descriptions of the cross sections for a right rectangular prism with a base measuring 15 inches by 8 inches and an unspecified height would be as follows:

A cross section parallel to the base will have the same dimensions as the base, which is 15 inches by 8 inches.

A cross section perpendicular to the base through the midpoints of the 8-inch sides forms a rectangle, but since the heights have not been provided for the prism, it cannot be defined specifically.

If a cross section is perpendicular to the base but no other information is provided, the dimensions of the cross section cannot be fully determined.

However, based on the options given, we can discern the following:

Option 2 is correct because a cross section parallel to the base would be identical to the base, measuring 15 inches by 8 inches.

Option 4 is correct since it specifies a rectangle measuring 6 inches by 15 inches assuming the height of the prism is 6 inches.

Options 1, 3, 5, and 6 cannot be determined to be correct without additional information regarding the height or manner of the cuts. Specifically, option 6 describes a cross section not parallel to the base but does not provide enough information about the shape or dimensions beyond the length being greater than 15 inches.

Answer:

A newsletter publisher believes that 49% of their readers own a Rolls Royce. Is there sufficient evidence at the 0.05 level to refute the publisher's claim? State the null and alternative hypotheses for the above scenario.

Null hypothesis ⇒ H₀: p = 0.49

Alternative hypothesis ⇒ Hₐ: p ≠ 0.49

Step-by-step explanation:

Given that α = 0.05

From the given information, the null and alternative hypothesis is expressed below:

Null hypothesis ⇒ H₀: p = 0.49

Alternative hypothesis ⇒ Hₐ: p ≠ 0.49