Answer:
Step-by-step explanation:
Hello!
The variable of interest is
X: the amount of coffee a person drinks per day. (ounces)
This variable has a normal distribution with μ= 15 ounces and σ=4.5 ounces.
10 randomly selected persons where surveyed.
a) X~N(μ;σ²) ⇒ X~N(15;20.25)
b) The sample means has the same distribution as the original variable except that the population variance is affected by the sample size:
X[bar]~N(μ;σ²/n) ⇒ X[bar]~N(15;20.25/10) ⇒ X[bar]~N(15;2.025)
c)
You need to find the probability that one random person drinks between 14.5 and 16.5 ounces of coffee per day, symbolically:
P(14.5 ≤ X ≤ 16.5)
For this part, since you need to calculate the probability that one person drinks between 14.5 and 16.5 ounces of coffee daily out of the whole population of people that drink coffee, you have to work using the distribution of the variable:
X~N(15;20.25)
To reach the correspondent probability you have to first standardize both bonds of the interval using Z=(X-μ)/δ~N(0;1):
P(14.5 ≤ X ≤ 16.5)
P(X ≤ 16.5) - P(X ≤ 14.5)
P(Z≤ (16.5-15)/4.5) - P(Z≤ (14.5-15)/4.5)
P(Z≤ 0.33) - P(Z≤ -0.11)= 0.62930 - 0.45620= 0.1731
d)
In this item, you need to calculate the probability that one out of the ten people surveyed drinks on average between 14.5 and 16.5 ounces of coffee.
P(14.5 ≤ X[bar] ≤ 16.5)
To calculate the correspondent probability you have to work using the distribution od the sample mean: X[bar]~N(15;2.025) and the standard normal: Z=(X[bar]-μ)/(δ/√n)~N(0;1)
P(X[bar] ≤ 16.5) - P(X[bar] ≤ 14.5)
P(Z≤ (16.5-15)/1.42) - P(Z≤ (14.5-15)/1.42)
P(Z≤ 1.06) - P(Z≤ -0.35)= 0.85543 - 0.36317= 0.49226
e)
Yes. Without the assumption that the variable had a normal distribution, you wouldn't be able to use the standard normal distribution to calculate the asked probabilities.
There is a possibility to apply the Central Limit Theorem to approximate the sampling distribution to normal if the sample was large enough (n ≥30) which is not the case.
f)
You need to find the IQR for the average consumption of coffee for a sample of 10 persons.
For this, you have to work using the distribution of the sample mean X[bar]~N(15;2.025)
The 1st quartile is the value that divides the bottom 25% of the distribution from the top 75%, symbolically:
P(X[bar]≤x[bar]₀)= 0.25
First, you have to determine the value of Z that accumulates 0.25 of probability:
P(Z≤z₀)= 0.25
z₀= -0.674
Now using the formula Z=(X[bar]-μ)/(δ/√n), you have to "reverse" the standardization, i.e. clear the value of X[bar]:
z₀=(x[bar]₀-μ)/(δ/√n)
-0.674=(x[bar]₀-15)/1.42
-0.674*1.42= (x[bar]₀-15)
x[bar]₀= (-0.674*1.42)+15
1st Quartile x[bar]₀= 14.0429 ounces
The third quartile is the value that divides the bottom 75% of the distribution from the top 25% of it:
P(X[bar]≤x[bar]₀)= 0.75
As before, the first step is to determine the corresponding value of Z:
P(Z≤z₀)= 0.75
z₀= 0.674
z₀=(x[bar]₀-μ)/(δ/√n)
0.674= (x[bar]₀-15)/1.42
0.674*1.42= x[bar]₀-15
x[bar]₀= (0.674*1.42)+15
3rd Quartile x[bar]₀= 15.9571
The IQR is the difference between Q3 and Q1:
IQR= 15.9571 - 14.0429= 1.9142
I hope this helps!
Christian and Tanae both leave Disneyland at the same time. Christian travels north at 65 mph. Tanae travels south at 55 mph
apart? Which of the following equations would you use to solve this word problem?
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.
Equation: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.
Learn more about equation here:https://brainly.com/question/2972832
#SPJ2
Given: ∠8 ≅ ∠16
Which lines must be parallel?
A) r and s
B) p and q
C) p and r
D) q and s
Hurry I need this one quick I don’t have a lot of time
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).
My computer is not letting me take a good quality of picture, but explanation and answer ?
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.
There are 157 college students interviewed about their work schedules. 85 of them work during the day. 43 of them work nightshift. 28 students work both. How many work old dayshift?
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
What is/are the factor(s) in the "Sub-U-Like" study?
A. 30-second, 60-second and 90-second commercials
B. The number of students
C. Craving for Sub-U-Like
D. The length of the television program
E. Length and frequency of the commercial.
F. One, three, or five commercials during the 50-minute television program
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
Solve the following:
1)If 32x=2, find x
2) simplify 9-1\2
Answer:
the answers are
1) 1/16
2) -18
Answer:
[tex]1)32x = 2 \\ \frac{32x}{32} = \frac{2}{32} \\ x = \frac{1}{16} [/tex]
[tex]2)9 - \frac{1}{2} \\ \frac{9}{1} \frac{ \times }{ \times } \frac{2}{2} - \frac{1}{2} \\ \frac{18}{2} - \frac{1}{2} \\ = \frac{17}{2} \\ = 8 \frac{1}{2} [/tex]
"The Crunchy Potato Chip Company packages potato chips in a process designed for 10.0 ounces of chips with an upper specification limit of 10.5 ounces and a lower specification limit of 9.5 ounces. The packaging process results in bags with an average net weight of 9.8 ounces and a standard deviation of 0.12 ounces. The company wants to determine if the process is capable of meeting design specifications."
Answer:
The process does not meets the specifications.
Step-by-step explanation:
It is provided that the Crunchy Potato Chip Company packages potato chips in a process designed for 10.0 ounces of chips.
The value of upper specification limit is, USL = 10.5 ounces.
The value of lower specification limit is, LSL = 9.5 ounces.
The mean weight of the chips bags is, [tex]\bar X=9.8\ ounces[/tex].
And the standard deviation weight of the chips bags is, [tex]\sigma=0.12\ ounces[/tex].
Compute the value of process capability as follows:
[tex]C_{p_{k}}=min \{C_{p_{L}},\ C_{p_{U}}\}[/tex]
Compute the value of [tex]C_{p_{L}}[/tex] as follows:
[tex]C_{p_{L}}=\frac{\bar X-LSL}{3 \sigma}=\frac{9.8-9.5}{3\times 0.12}=0.833[/tex]
Compute the value of [tex]C_{p_{K}}[/tex] as follows:
[tex]C_{p_{K}}=\frac{USL-\bar X}{3 \sigma}=\frac{10.5-9.8}{3\times 0.12}=1.944[/tex]
The value of process capability is:
[tex]C_{p_{k}}=min \{C_{p_{L}},\ C_{p_{U}}\}[/tex]
[tex]=min\{0.833,\ 1.944\}\\=0.833[/tex]
The value of process capability lies in the interval 0 to 1. So the process is not capable of meeting design specifications.
Thus, the process does not meets the specifications.
Final answer:
The process capability of The Crunchy Potato Chip Company's packaging process has been questioned. By calculating the process capability index (Cpk), we find that the process capability is below the desirable threshold, suggesting that the process might not consistently meet the specified design requirements.
Explanation:
The student's query pertains to the process capability of The Crunchy Potato Chip Company's packaging process. This concept is part of quality control in process management and is measured by the process capability index (Cpk). In this case, the company has set specifications for a bag to contain between 9.5 and 10.5 ounces of chips and aims to have an average of 10.0 ounces. However, with a mean of 9.8 ounces and a standard deviation of 0.12 ounces, we need to calculate whether the process falls within the acceptable limits and how often it meets design specifications. To do this, the Cpk value is computed, which considers the mean, standard deviation, and the proximity of the mean to the closest specification limit.
Calculating the Process Capability Index (Cpk)
The formula for Cpk is:
Cpk = minimum of [(USL - mean) / (3 * sigma), (mean - LSL) / (3 * sigma)]
Where:
USL = Upper Specification Limit
LSL = Lower Specification Limit
mean = average net weight of the bags
sigma = standard deviation
Here, USL is 10.5 ounces, LSL is 9.5 ounces, mean is 9.8 ounces, and sigma is 0.12 ounces. Substituting these values:
Cpk = minimum of [(10.5 - 9.8) / (3 * 0.12), (9.8 - 9.5) / (3 * 0.12)]
Cpk = minimum of [1.9444, 0.8333]
The smaller of the two results is 0.8333, indicating that this is the Cpk value. A Cpk of 1.33 or higher is generally considered good, while a Cpk less than 1 indicates that the process may not be capable of meeting design specifications consistently. In this case, with a Cpk of 0.8333, The Crunchy Potato Chip Company's process may need improvement.
Suppose the selling price of homes is skewed right with a mean of 350,000 and a standard deviation of 160000 If we record the selling price of 40 randomly selected US homes what will be the shape of the distribution of sample means what will be the mean of this distribution what will be the standard deviation of this distribution
Answer:
The distribution will be approximately normal, with mean 350,000 and standard deviation 25,298.
Step-by-step explanation:
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.
Population:
Suppose the selling price of homes is skewed right with a mean of 350,000 and a standard deviation of 160000
Sample of 40
Shape approximately normal
Mean 350000
Standard deviation [tex]s = \frac{160000}{\sqrt{40}} = 25298[/tex]
The distribution will be approximately normal, with mean 350,000 and standard deviation 25,298.
Answer:
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]
The mean would be:
[tex] \mu_{\bar X} =350000[/tex]
And the standard deviation would be:
[tex]\sigma_{\bar X} =\frac{160000}{\sqrt{40}}= 25298.221[/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 selling price of a population, and for this case we know the following info
Where [tex]\mu=350000[/tex] and [tex]\sigma=160000[/tex]
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".
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]
The mean would be:
[tex] \mu_{\bar X} =350000[/tex]
And the standard deviation would be:
[tex]\sigma_{\bar X} =\frac{160000}{\sqrt{40}}= 25298.221[/tex]
You are a personnel director and are interested in predicting the Number of Shares of Company Stock (Y) using the Number of Years Employed with the Company (X). You randomly selected 8 employees and found that the average number of shares is 525 and the average number of years employed is 22.5. If the slope (b1) is 20.0, what is the least squares estimate of the intercept (b0)
Answer:
intercept=b0=75
Step-by-step explanation:
The least squares estimate of the intercept b0 can be computed as
b0=ybar-b1*xbar.
ybar=average number of shares of company stock=525.
xbar= average number of years employed=22.5.
slope=b1=20.
Thus,
intercept=b0=ybar-b1*xbar
intercept=b0=525-20*22.5
intercept=b0=525-450
intercept=b0=75.
Thus, the estimate of intercept b0=75.
can someone help me with this
Convert 100 USD to rubles. Use exchange rate, where 1 USD equals 32.5 rubles.
Answer:
3250 rubles.
Step-by-step explanation:
1 USD = 32.5 rubles so...
1 * 100 USD = 32.5 * 100 rubles.
The answer is 3250 rubles.
Answer:
3250 rubles
Step-by-step explanation:
1 USD = 32.5 rubles
100 USD = 100 × 32.5
= 3250 rubles
I think c is the right answer am I correct ?
Answer: yes
-5 is not greater than 4
-5
Step-by-step explanation:
Decompose 0.42 into tenths and hundredths
Answer:
0.40 + 0.02
Step-by-step explanation:
4 tenths plus 2 hundredths
The two dot plots represent a sample of the number of
people in households in two towns. Which statements
are true about the data sets?
Check all that apply.
Both have the same number of data points.
Both means are between 3 and 4.
O Both have the same median.
Both have the same range.
Westwood has less variability than Middleton.
The answer is:
Both have the same number of data points
Both means are between 3 and 4
Westwood has less variability than Middleton
Answer:
The right anwers are : A B and E
Step-by-step explanation:
right on edg!
7 divided by 4 long division
A recent survey in the N.Y. Times Almanac indicated that 48.8% of families own stock. A broker wanted to determine if this survey could be valid. He surveyed a random sample of 250 families and found that 142 owned some type of stock. At the 0.05 significance level, can the survey be considered to be accurate?
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%.
Null Hypothesis: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%.
Learn more about the topic Null Hypothesis:
https://brainly.com/question/24449949
Shawndra said that it is not possible to draw a trapezoid that is a rectangle, Explain your answer using the properties of quadrilaterals. Help FAST please. TELL ME WHAT TO DO AND SAY 30 points
Answer:
She is wrong
Rectangle can be a trapezoid
Step-by-step explanation:
A trapezoid is a quadrilateral which has atleast one pair of parallel sides.
A rectangle has two pairs of parallel sides, so it is a trapezoid too.
All rectangles are trapezoid.
But all trapezoids are not rectangles
Factorize 12x² + 15xy
Answer:
[tex]12 {x}^{2} + 15xy \\ = 3x(4x +5 y)[/tex]
hope this helps you...
SurveyMonkey is a popular website for hosting online surveys and from time to time they will also create surveys based on a subject they are interested in answering questions about. Given the widespread adoption of dating sites and apps, they wanted to learn how people feel about them. It was found that out of 400 responses, 100 have used or are currently using online dating services. The average age of those that were using online dating services was 35 years old with a sample standard deviation of 12 years. What distribution should you use to compute a confidence interval for the average age of people using online dating services
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
The price-earnings (PE) ratios of a sample of stocks have a mean value of 10.5 and a standard deviation of 3. If the PE ratios have a normal distribution, use the Empirical Rule (also called the 68-95-99.7 Rule) to estimate the percentage of PE ratios that fall between:
Answer:
a) 68% falls within 7.5 and 13.5
b) 95% falls within 4.5 and 16.5
c) 99.7% falls within 1.5 and 19.5
Step-by-step explanation:
Given that:
mean (μ) = 10.5, Standard deviation (σ) = 3.
The Empirical Rule (also called the 68-95-99.7 Rule) for a normal distribution states that all data falls within three standard deviations. That is 68% falls within the first standard deviation (µ ± σ), 95% within the first two standard deviations (µ ± 2σ), and 99.7% within the first three standard deviations (µ ± 3σ).
Therefore using the empirical formula:
68% falls within the first standard deviation (µ ± σ) = (10.5 ± 3) = (7.5, 13.5)
95% within the first two standard deviations (µ ± 2σ) = (10.5 ± 2(3)) = (10.5 ± 6) = (4.5, 16.5)
99.7% within the first three standard deviations (µ ± 3σ) = (10.5 ± 3(3)) = (10.5 ± 9) = (1.5, 19.5)
We are interested in determining whether the variances of the sales at two music stores (A and B) are equal. A sample of 25 days of sales at store A has a sample standard deviation of 30, while a sample of 16 days of sales from store B has a sample standard deviation of 20. At 95% confidence, the null hypothesis _____.
An eight-sided die, which may or may not be a fair die, has four colors on it; you have been tossing the die for an hour and have recorded the color rolled for each toss. What is the probability you will roll an orange on your next toss of the die? Express your answer as a simplified fraction or a decimal rounded to four decimal places.
Answer:
Probability of an Orange on the next toss
= (23/60) = 0.3833
Step-by-step explanation:
Orange: 46
Brown: 23
Green: 32
Yellow: 19
Probability of an Orange on the next toss
= n(orange colours obtained in the tosses) ÷ n(number of tosses)
n(orange colours in the tosses) = 46
Total number of tosses = 46 + 23 + 32 + 19
= 120.
Probability of an Orange on the next toss
= (46/120) = (23/60) = 0.3833
Hope this Helps!!!!
You spin the spinner shown below once. Each sector shown has an equal area.
What is p (not squirrel)
Answer: 0.8
Step-by-step explanation:
There are 5 possible equally sized sections meaning there is a 0.2 or 20% of landing on each section. We can subtract the probability of getting a squirrel from the whole thing (1 as probability always equals 1) to determine the probability of not squirrel.
P(squirrel) = 0.2
1 - P(squirrel) = P(not a squirrel)
1 - 0.2 = 0.8
Answer: the anserw is 0.8
Step-by-step explanation:
Write the equation of the line that goes through the point (-4,7) and has a slope of -5.
Answer:
y= -5x-13
Step-by-step explanation:
start with the linear equation
y= mx+b
indentify what you already have.
x= -4 and y= 7 and m(slope)= -5
We are solving for b, so plug in what you have.
7= -5(-4)+b
Simplify.
7= 20+b
Subtract 20 on both sides.
-13= b
Rewrite your equation with the x and y values.
y= -5x-13
A sample of 16 elements is selected from a population with a reasonably symmetrical distribution. The sample mean is 100 and the sample standard deviation is 40. We can say that we are 90% confident that is between what two numbers? 12. What is the upper number? Maintain three decimal points in your calculations and give at least two decimal points in your answer.
Answer:
We can say that we are 90% confident that the population mean is between 29.876 and 170.124.
The upper number is 170.124.
Step-by-step explanation:
We have the sample's standard deviation, so we use the students' t-distribution to solve this question.
The first step to solve this problem is finding how many degrees of freedom, we have. This is the sample size subtracted by 1. So
df = 16 - 1 = 15
90% confidence interval
Now, we have to find a value of T, which is found looking at the t table, with 15 degrees of freedom(y-axis) and a confidence level of [tex]1 - \frac{1 - 0.9}{2} = 0.95([tex]t_{95}[/tex]). So we have T = 1.7531
The margin of error is:
M = T*s = 40*1.7531 =70.124
In which s is the standard deviation of the sample.
The lower end of the interval is the sample mean subtracted by M. So it is 100 - 70.124 = 29.876
The upper end of the interval is the sample mean added to M. So it is 100 + 70.124 = 170.124
We can say that we are 90% confident that the population mean is between 29.876 and 170.124.
The upper number is 170.124.
Answer:
[tex]100-1.753\frac{40}{\sqrt{16}}=82.470[/tex]
[tex]100+ 1.753\frac{40}{\sqrt{16}}=117.530[/tex]
So on this case the 90% confidence interval would be given by (82.470;117.530)
And the upper value would be 117.530 for this case
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=100[/tex] represent the sample mean
[tex]\mu[/tex] population mean (variable of interest)
s=40 represent the sample standard deviation
n=16 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 critical value [tex]t_{\alpha/2}[/tex] we need to find first the degrees of freedom, given by:
[tex]df=n-1=16-1=15[/tex]
Since the Confidence is 0.90 or 90%, the value of [tex]\alpha=0.1[/tex] and [tex]\alpha/2 =0.05[/tex], and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.05,15)".And we see that [tex]t_{\alpha/2}=1.753[/tex]
Now we have everything in order to replace into formula (1):
[tex]100-1.753\frac{40}{\sqrt{16}}=82.470[/tex]
[tex]100+ 1.753\frac{40}{\sqrt{16}}=117.530[/tex]
So on this case the 90% confidence interval would be given by (82.470;117.530)
Which statements are true about a decagonal (10-sided) pyramid? Check all that apply.
It has one face that is a decagon.
It has two faces that are decagons.
It has 11 faces.
It has 20 edges.
It has 20 vertices.
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:
what is factored form of x2-12x-4?
Answer:
The expression is not factorable with rational numbers...
Step-by-step explanation:
The same researcher wants to see if recently widowed spouses leave the house more after they perform some activity (e.g., Bingo, Support Group, etc.). She wants to compare participants before and after a group activity. Which type of t-test should she use?
Answer:
paired t-test
Step-by-step explanation:
Paired t-test is used to measure before and after effect. For example, a researcher wants to check the effect of new teaching method and he wants to compares marks of students before new teaching method and marks of students before new teaching method.
In the given example there are two groups participants before group activity and participants after group activity. A researcher wants to investigate that whether recently widowed spouses leave house after performing group activity or not. The observations in these two groups are paired naturally and we take the differences of these two groups are considered as random sample. This type of t-test is known as paired t-test.
inDJKL side JK measures 10.6 inches side KL measures 7 inches inside JL measures 5 inches based on the information that is provided which could be a correct set of angles measured for these sides?
angle J= 23.2 angle K equals 33.5 angle owl equals 23.2
angle J equals 23.2 angle K equals 33.5 angle L equals 123.2
angle J equals 123.2 angle K equals 23.2 angle L equals 33.5
angle J equals 33.5 angle K equals 23.2 angle L equals 123.2
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! ;)
The mean salary of people living in a certain city is $37,500 with a standard deviation of $2,119. A sample of n people will be selected at random from those living in the city. Find the smallest sample size n that will guarantee at least a 90% chance of the sample mean income being within $500 of the population mean income.
Answer:
The smallest sample size needed is 49.
Step-by-step explanation:
We have that to find our [tex]\alpha[/tex] level, that is the subtraction of 1 by the confidence interval divided by 2. So:
[tex]\alpha = \frac{1-0.9}{2} = 0.05[/tex]
Now, we have to find z in the Ztable as such z has a pvalue of [tex]1-\alpha[/tex].
So it is z with a pvalue of [tex]1-0.05 = 0.95[/tex], so [tex]z = 1.645[/tex]
Now, find the margin of error M as such
[tex]M = z*\frac{\sigma}{\sqrt{n}}[/tex]
In which [tex]\sigma[/tex] is the standard deviation of the population and n is the size of the sample.
Find the smallest sample size n that will guarantee at least a 90% chance of the sample mean income being within $500 of the population mean income.
This is n for which [tex]M = 500, \sigma = 2119[/tex]
So
[tex]M = z*\frac{\sigma}{\sqrt{n}}[/tex]
[tex]500 = 1.645*\frac{2119}{\sqrt{n}}[/tex]
[tex]500\sqrt{n} = 1.645*2119[/tex]
[tex]\sqrt{n} = \frac{1.645*2119}{500}[/tex]
[tex](\sqrt{n})^{2} = (\frac{1.645*2119}{500})^{2}[/tex]
[tex]n = 48.6[/tex]
Rounding up
The smallest sample size needed is 49.
Answer:
[tex]n=(\frac{1.640(2119)}{500})^2 =48.31 \approx 49[/tex]
So the answer for this case would be n=49 rounded up to the nearest integer
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=37500[/tex] represent the sample mean for the sample
[tex]\mu[/tex] population mean (variable of interest)
[tex]\sigma=2119[/tex] represent the sample standard deviation
n represent the sample size
Solution to the problem
The margin of error is given by this formula:
[tex] ME=z_{\alpha/2}\frac{\sigma}{\sqrt{n}}[/tex] (a)
And on this case we have that ME =500 and we are interested in order to find the value of n, if we solve n from equation (a) we got:
[tex]n=(\frac{z_{\alpha/2} \sigma}{ME})^2[/tex] (b)
The critical value for 90% of confidence interval now can be founded using the normal distribution. And in excel we can use this formla to find it:"=-NORM.INV(0.05;0;1)", and we got [tex]z_{\alpha/2}=1.640[/tex], replacing into formula (b) we got:
[tex]n=(\frac{1.640(2119)}{500})^2 =48.31 \approx 49[/tex]
So the answer for this case would be n=49 rounded up to the nearest integer