The Price of kiwis can be deterrent by the equation P=1.15n where p is the price and n is the number of kiwis. What is the constant of proportionality (unit rate)?

Answer:

C

Step-by-step explanation:

If the line is parallel that means 1.2 has to be the same. And passing through (5,0) means a plus five.

Answer:

a) The null hypothesis is

H₀: μ₀ = 3 inches

And the alternative hypothesis is

Hₐ: μ₀ ≠ 3 inches

b) Check Explanation.

c) The $3000 is obviously the cost of a type I error.

Step-by-step explanation:

For hypothesis testing, the first thing to define is the null and alternative hypothesis.

The null hypothesis plays the devil's advocate and is always about the absence of significant difference between two proportions being compared. It usually maintains that random chance is responsible for the outcome or results of any experimental study/hypothesis testing. It usually contains the signs =, ≤ and ≥ depending on the directions of the test.

While, the alternative hypothesis takes the other side of the hypothesis; that there is indeed a significant difference between two proportions being compared. It usually confirms the the theory being tested by the experimental setup. It usually maintains that other than random chance, there are significant factors affecting the outcome or results of the experimental study/hypothesis testing. It usually contains the signs ≠, < and > depending on the directions of the test.

For this question, we want to verify that the mean diameter produced by the machine is really off-target.

Note that, that target is 3 inches.

Hence, the null hypothesis will be that that there is no difference between the mean diameter of the 100 cylinders sampled and the target of 3 inches.

And the alternative hypothesis will confirm the concerns of the technical staff that there is a significant difference between the mean diameter of the 100 cylinders sampled and the target diameter of 3 inches. That is, the mean diameter is off-target.

Mathematically,

The null hypothesis is

H₀: μ₀ = 3 inches

And the alternative hypothesis is

Hₐ: μ₀ ≠ 3 inches

b) A type I error involves rejecting the null hypothesis and accepting the alternative hypothesis when in reality, the null hypothesis is true. It involves saying there is significant evidence to show that the mean diameter of the sampled cylinders is indeed different from the targeted 3 in. (that is, the mean diameter of sampled cylinders is off-target), so they try to fix the issue when in reality, there is actually no significant difference between the mean diameter of sampled cylinders and the targeted 3 inches.

While a type II error involves failing to reject the null hypothesis when in reality it should have been rejected.

It entails not rejecting the null hypothesis and making conclusions based on the null hypothesis, when in reality, the alternative hypothesis should have been accepted together with its conclusion.

In this one the firm would conclude that they do not need to change anything as there is no significant difference between the mean diameter of the sampled cylinders and the targeted 3 inches, when in reality, there is a significant difference between the mean diameter of the sampled cylinders and the targeted 3 inches diameter.

c) The $3000 is obviously the cost of a type I error.

This is because the type I error is the one that involves tryin to fix the problem that did not even exist in reality.

Hope this Helps!!!

Answer:

Step-by-step explanation:

An Automobile Parts supplier owns a machine that produces a cylindrical engine part. The part is supposed to have an outside diameter of 3 inches in order for customers requirements to be met.

Lately, the company has been producing cylindrical engine parts with diameters that are either < 3inches or > 3inches. Technical staff feel that the mean diameter produced by the machine, from a random sample of 100 engine parts is not equal to 3 inches. The parts supplier wishes to set up a hypothesis test so that the problem-solving team can swing into action if or when the Null Hypothesis is rejected.

The null hypothesis is:

100 Cylindrical Engine Parts have a mean diameter = 3 inches

The alternative hypothesis is:

100 Cylindrical Engine Parts have a mean diameter that is NOT equal to 3 inches

[You can input the "not equal to" sign]

If the null hypothesis is rejected after statistical procedures, the supplier will proceed to employ the services of the problem-solving team!

Based on the converse of the Corresponding Angles Theorem, if ∠8 ≅ ∠16, then the lines that must be parallel are: A) r and s.

What is the converse of corresponding angles theorem?

If two lines are cut by a transversal, and the corresponding angles are congruent, then the lines are parallel, which is the converse of the Corresponding Angles Theorem.

In the image below, angles 8 and 16 are said to be congruent to each other, and both lie on lines r and s.

Therefore, based on the converse of the Corresponding Angles Theorem, lines r and s must be parallel (option A).

Answer:

The expression is not factorable with rational numbers...

Step-by-step explanation:

Answer: Angle J = 33.5°, angle K = 23.2°, angle L = 123.2°

Step-by-step explanation: i did the quiz and got it correct :D

YAHOO!!! YOU ARE CORRECT!!! LETS GIVE HIM AROUND OF APPLAUSE!!!

So thats why its "angle J equals 33.5 angle K equals 23.2 angle L equals 123.2" is the last option! (D.) U R smart, Einstein! ;)

Answer:

There will be 6 buses needed; the number of buses has to be a whole number.

Step-by-step explanation:

So we know that there is 232 people, and each bus holds 44 people. To find how many buses we need, you divide 232/44. Then, you get 5 with 12 extra. So you add one more bus, but that bus isn't full; there will only be 12 people inside it.

The reason why the number of buses has to be a whole number is because a bus has to be a whole bus, even though the bus isn't full. The maximum capacity of the bus is 44, but you can have 12 people inside it.

Answer:

Step-by-step explanation:

Answer:

The Answer is B.

Step-by-step explanation:

I took the test on Edg 2021 and got it right the first time.

Answer:

B. It has two faces that are decagons.

D. It has 20 edges.

E. It has 20 vertices.

Answer:b,d and e

Step-by-step explanation:

Answer:

0.40 + 0.02

Step-by-step explanation:

4 tenths plus 2 hundredths

Answer: yes

-5 is not greater than 4

-5

Step-by-step explanation:

Answer:

QS + QR > RS

QR + RS > QS

RS + QS > QR

Step-by-step explanation:

JUST TOOK THE TEST

The complete Triangle Inequality is

The triangle inequality theorem defines the relationship between a triangle's three sides. The total of the lengths of the two sides of any triangle is always greater than the length of the third side, according to this theorem. In other words, the shortest distance between two unique points is always a straight line, according to this theorem.

According to Triangle Inequality " the sum of two side of the triangle is greater than the third side of Triangle."

Then, applying Triangle Inequality

QS + QR > RS

QR + RS > QS

RS + QS > QR

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Answer:

y = 6x-4

Step-by-step explanation:

The slope intercept form of a line is

y = mx+b where m is the slope and b is the y intercept

We know the slope is 6 and the y intercept is -4

y = 6x + -4

y = 6x-4

Slope-intercept form: y = mx + b (m = slope and b = y-intercept)

Slope (m) = 6

y-intercept (b) = -4

Put into its final form.

y = 6x - 4

Best of Luck!

Answer:

3/5 then 11/5

Step-by-step explanation:

These symbols "I  I" represent absolute values.

11/5 equals to 2 1/5

3/5 is less than 2 1/5

Answer:

65t+55t=540

Step-by-step explanation:

65 multiplied by four and a half equals 292.5

55 multiplied by four and a half equals 247.5

add together to get 540

If Christian travels north at 65 mph. The equations that you would  use to solve this word problem is: 65t+55t=540.

The equation will be: 65t+55t=540

Where:

t=time

65=Distance to north per hour

55=Distance to south per hour

540=Miles apart

Therefore the equations that you would  use to solve this word problem is: 65t+55t=540.

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Answer:

59/10

Step-by-step explanation:

5+9/10

50/10 + 9/10

=59/10

Answer:

it 59/10

Step-by-step explanation:

To determine the sample size needed for a 99% confidence interval with a maximum width of .18 for a coin flip experiment, we must rely upon statistical principles such as the law of large numbers and the relationship between sample size and confidence interval width. Although we cannot give a specific number without more details, it is generally true that a larger sample size (i.e., more coin flips) results in a narrower confidence interval.

Your question pertains to finding the necessary sample size for a particular width of a confidence interval in a coin-flip experiment. A confidence interval represents the range where we are certain that the parameter, in this case, the probability of getting a head, lies to a certain degree, say 99%. Narrowing down this interval or making it smaller would require a larger number of coin flips or trials. The probable outcome of our experiment does indeed align with the theoretical probability when a large number of trials is conducted, which is also known as the law of large numbers.

The calculation of the size of a confidence interval involves standard deviation, confidence level (z-score) and sample size. By adjusting these parameters, we can alter the size of a confidence interval. For example, a 90% confidence interval would be smaller compared to a 95% interval due to the decreased degree of certainty. However, without exact numbers we cannot directly calculate how many flips are required for a 99% confidence interval of a certain width.

As a general rule of thumb, when conducting confidence interval tests, it would be safe to suggest that a larger sample size (which for a coin flip experiment would mean more coin flips) will result in a narrower confidence interval. Therefore, to achieve a 99% confidence interval of width at most .18, one would need net a large number of trials, or flips.

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Answer:

11x-y

Step-by-step explanation:

You add 8x+3x and get 11x then you put the equation together

11x-y

HOPE THIS HELPS!!!

Answer:

The p-value should be smaller than 0.05.

Step-by-step explanation:

We know that the 95% confidence interval for the difference of means is (5.6, 10.2). As the lower bound is larger than 0, we are 95% confident that the reduction program had had a effect in the blood pressure level.

Then, as the program had a significant effect in the blood pressure level, we know that the null hypothesis (that states that the blood pressure levels would no change significantly) is then rejected.

If the significance level is 0.05, according to the confidence of the interval, to reject the null hypothesis, the p-value had to be lower than the significance level. In conclusion, the p-value should be lower than 0.05.

Answer:

[tex] p_v= 0.01[/tex]

Since the significance level is 0.05 we see that [tex]pv<\alpha[/tex] so we have enough evidence to reject the null hypothesis. And the best conclusion for this case would be:

b. at least some, but not all, of the gestation periods across all four species are the same

Because is only to identify if AT LEAST one mean is different, NOT to conclude that the all the means are different.

Step-by-step explanation:

Previous concepts

Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".  

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"  

Solution to the problem

The hypothesis for this case are:

Null hypothesis: [tex]\mu_{A}=\mu_{B}=\mu_{C}= \mu_D[/tex]

Alternative hypothesis: Not all the means are equal [tex]\mu_{i}\neq \mu_{j}, i,j=A,B,C,D[/tex]

In order to find the mean square between treatments (MSTR), we need to find first the sum of squares and the degrees of freedom.

If we assume that we have [tex]p=4[/tex] groups and on each group from [tex]j=1,\dots,p[/tex] we have [tex]n_j[/tex] individuals on each group we can define the following formulas of variation:  

[tex]SS_{total}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x)^2 [/tex]  

[tex]SS_{between}=SS_{model}=\sum_{j=1}^p n_j (\bar x_{j}-\bar x)^2 [/tex]  

[tex]SS_{within}=SS_{error}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x_j)^2 [/tex]  

And we have this property  

[tex]SST=SS_{between}+SS_{within}[/tex]  

And in order to test this hypothesis we need to ue an F statistic and for this case the p value calculated is

[tex] p_v= 0.01[/tex]

Since the significance level is 0.05 we see that [tex]pv<\alpha[/tex] so we have enough evidence to reject the null hypothesis. And the best conclusion for this case would be:

b. at least some, but not all, of the gestation periods across all four species are the same

Because is only to identify if AT LEAST one mean is different NOT to conclude that the all the means are different.

The correct option is (d)not all of the average gestation periods are the same across all four species.

In a test of hypothesis, the test statistic is a function of the sample data used to decide whether or not to reject the null hypothesis.

Given that,

[tex]\alpha=0.05\\p-value=0.009[/tex]

[tex]H_0:[/tex]The average gestation period is the same for each of the four spices.

Since the p-value is less than the value of the [tex]\alpha[/tex].

So, we reject the [tex]H_0[/tex]

Not all of the average gestation periods are the same across all four species.

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Answer:

E. Length and frequency of the commercial.

Remaining Details of the Question:

A study investigated the effect of the length and the repetition of TV advertisements on students' desire to eat at a Sub-U-Like sandwich franchise. Sixty students watched a 50- minute television program that showed at least one commercial for Sub-U-Like during advertisement breaks. Some students saw a 30-second commerical, some saw a 60-second commercial, others a 90-second commerical. The same commerical was shown one, three, or five times during the program. After the viewing, each student was asked to rate their craving for a Sub-U-Like sandwich from the set ("Don't want to eat", "Neutral", "Want to eat"}

Explanation:

During the course of an experimental study, it is important to identify the variables of interest. These variables are referred to as the factors. Factors are controlled independent variables in an experimental study that can be manipulated by the experimenter.

In this case, it was indicated that the study investigated the effect of the length and the repetition of TV advertisements on students' desire to eat at a Sub-U-Like sandwich franchise. Therefore, the factors in the "Sub-U-Like" study are length and frequency of the commercial.

Final answer:

The factors in the "Sub-U-Like" study include the length and frequency of the commercial, the number of students, and the number of commercials during the TV program. Factors in the "Sub-U-Like" study, while not explicitly defined in the examples provided, can generally include variables such as length and frequency of commercials and the number of commercials shown, all of which can influence viewers' behaviors and perceptions in psychological or marketing research.

Explanation:

Factors in the "Sub-U-Like" study:

Factor A: Length and frequency of the commercial

Factor B: The number of students

Factor F: One, three, or five commercials during the 50-minute television program

Answer:

9/35

Step-by-step explanation:

-1/7 ÷ -5/9

Copy dot flip

-1/7 * -9/5

Multiply the numerators

-1*-9 = 9

Multiply the denominators

7*5 = 35

9/35

Step-by-step explanation:

[tex]\frac{-\frac{1}{7} }{-\frac{5}{9} }[/tex]

Invert the fraction in the denominator and multiply it by the fraction in the numerator.

[tex](-\frac{1}{7} )(-\frac{9}{5} )\\\\\frac{9}{35}[/tex]

Answer:

So we use the t-distribution to compute a confidence interval for the average age of people using online dating services

Step-by-step explanation:

Confidence interval for a mean.

We have to decide between the t-distribution and the z-distribution.

T-distribution: We use the sample standard deviation.

Z-distribution: We use the population standard deviation.

In this problem:

The average age of those that were using online dating services was 35 years old with a sample standard deviation of 12 years.

So we use the t-distribution to compute a confidence interval for the average age of people using online dating services

Step-by-step explanation:

No of students work during day shift = 85

No of students work during night shift = 43

No of students working both shift = 28

So first we will divide 28 by 2 = 14

Then it means there were 14 students working in day shift and 14 students working in night shift

Total number of students work during day shift = 85 + 14 = 99

Answer:

Part a

Null hypothesis: [tex]\mu =30[/tex]

Part b

Alternative hypothesis: [tex]\mu \neq 30[/tex]

Part c

Alternative hypothesis: [tex]\mu > 30[/tex]

Part d

Alternative hypothesis: [tex]\mu < 30[/tex]

Step-by-step explanation:

Previous concepts

A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".  

The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".  

The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".  

Solution to the problem

For this case we want to test if the true mean is equal to 30 or no.

Part a

Null hypothesis: [tex]\mu =30[/tex]

Part b

Alternative hypothesis: [tex]\mu \neq 30[/tex]

Part c

Alternative hypothesis: [tex]\mu > 30[/tex]

Part d

Alternative hypothesis: [tex]\mu < 30[/tex]

Answer:

There is enough statistical evidence to support the claim that the survey is not accurate.

Step-by-step explanation:

We have  to perform a test of hypothesis on the proportion.

The claim is that the proportion of families that own stock differs from 48.8%.

Then, the null and alternative hypothesis are:

[tex]H_0: \pi=0.488\\\\H_a:\pi\neq0.488[/tex]

The significance level is 0.05.

The sample. of size n=250, has a proportion of p=0.568.

[tex]p=X/n=142/250=0.568[/tex]

The standard error of the proportion is

[tex]\sigma_p=\sqrt{\dfrac{\pi(1-\pi)}{n}}=\sqrt{\dfrac{0.488*0.512}{250}}=\sqrt{0.00099}=0.032[/tex]

The z-statistic can now be calculated:

[tex]z=\dfrac{p-\pi-0.5/n}{\sigma_p}=\dfrac{0.568-0.488-0.5/250}{0.032}=\dfrac{0.078}{0.032}=2.4375[/tex]

The P-value for this two-tailed test is then:

[tex]P-value=2*P(z>2.4375)=0.015[/tex]

As the P-value is smaller than the significance level, the effect is significant. The null hypothesis is rejected.

There is enough evidence to support the claim that the survey is not accurate.

The suffecient eveidence to insure that the percentage of families who won stock is different from 48.8%.

The hypothesis  that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error.

The null hypothesis can be stated as shown below:

[tex]H_{0} :P=48.8[/tex]%

That is, the percentage of families who own stock is [tex]48.8[/tex]%.

The alternative hypothesis can be stated as shown below:

[tex]H_{a} :p\neq 48.8[/tex]%

That is, the percentage of families who own stock is different from [tex]48.8[/tex]%

The [tex]z[/tex] test statistic is given below:

[tex]z=\frac{\hat{p-p}}{\sqrt{\frac{p\left ( 1-p \right )}{n}}}[/tex]

Here, [tex]\hat{p}[/tex] is the observed proportion then, [tex]\hat{p}[/tex] is calculated by,

[tex]\hat{p}=\frac{x}{n} \\=\frac{142}{250} \\=0.568[/tex]

Therefore,

[tex]z=\frac{\hat{p}-p}{\sqrt{\frac{p\left ( 1-p \right )}{n}}} \\=\frac{0.08}{0.0316}\\ =2.532[/tex]

Calculating the p-value be excel as attached below then we get,

The p-value is 0.01.

This p-value is called the actual level of significance.

The value of alpha is given as [tex]0.05[/tex]

Decision: The rejection of the null hypothesis [tex]H_0[/tex] because [tex]p-value < \alpha[/tex]

So, reject the null hypothesis.

Conclusion: The p-value is less than considered level of significance 5%.

Therefore the null hypothesis get rejected while the alternative hypotheisis is accepted.

Hence, there is suffecient eveidence to insure that the percentage of families who won stock is different from 48.8%.

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Answer:

Domain is where the function is defined.  In other words, all valid values of x that allows us to find y.

Range is values of y for the function.

Step-by-step explanation:

Here is the example of function [tex]y = \sqrt{x}[/tex], so domin is between 0 and positive infinity.  x cannot be negative.

The range is from 0 (because that's the lowest value of y) to positive infinity

Answer:

all nonzero real numbers for both of them

Step-by-step explanation:

e2021

Answer:

b) 74

The sample size that needs to be taken if the desired margin of error is 5 or less is 74

Step-by-step explanation:

Explanation:-

Given population variance σ² = 484

                                            σ = √484

                                            σ = 22

The level of significance ∝=0.95

The z-score of 0.95 level of significance = 1.96

Given Margin of error = 5

we know that the margin of error is determined by

[tex]M.E = \frac{Z_{\alpha }S.D }{\sqrt{n} }[/tex]

cross multiplication, we get

[tex]\sqrt{n} = \frac{Z_{\alpha }S.D }{M.E}[/tex]

[tex]\sqrt{n} = \frac{1.96 X22 }{5} = 8.624[/tex]

Squaring on both sides, we get

n = (8.624) ²

n = 74.37 ≅74

Conclusion:-

The sample size that needs to be taken if the desired margin of error is 5 or less is 74