Consider a binomial experiment with 16 trials and probability 0.60 of success on a single trial.
(a) Use the binomial distribution to find the probability of
exactly 10 successes.
(b) Use the normal distribution to approximate the probability of
exactly 10 successes.
(c) Compare the results of parts (a) and (b).
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Group 1: 4.2, 4.2, 3.4
Group 2: 4.5, 2.1, 2.3
Group 3: 1.2, 0.3, -0.3, 2.3
Use the Bonferronni method to test each of the 3 possible hypotheses at the 3% significance level.
(a) Find the value of the test statistic for each of the 3 possible hypotheses.
(b) Which pairs of means are significantly different (using the Bonferronni method at the 3% significance level?
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M&M'S MILK CHOCOLATE: 24% cyan blue, 20% orange, 16% green, 14% bright yellow, 13% red, 13% brown.
Confidence Interval for Small n
Choose the color of M&M’s you will be working with for this project
Color:
Using the collected data below from a single fun-sized bag, provide the frequency and proportion of M&M’s in your color of choice.
Red |
Orange |
Yellow |
Green |
Blue |
Brown |
2 |
1 |
2 |
3 |
5 |
1 |
Number of M&M's in your color:
Total number of M&M's:
Proportion of M&M's in your color:
Construct a 95% confidence interval for the proportion of M&M’s one can expect to find in the color of your choice.
Check the requirements for constructing a confidence interval for the proportion are satisfied. Show your work.
The conditions might not be satisfied, depending on how many candies were in your bag. If the conditions are not met, what could you do?
Part 2: Confidence Interval for Larger n
Now, use the data collected below from a collection of fun-sized bags to provide the frequency and proportion of M&M’s in your original color of choice.
Red |
Orange |
Yellow |
Green |
Blue |
Brown |
54 |
49 |
52 |
51 |
84 |
109 |
Number of M&M's in your color:
Total number of M&M's:
Proportion of M&M's in your color:
Construct a 95% confidence interval for the proportion of M&M’s one can expect to find in the color of your choice.
Write an interpretation of your confidence interval specific to your color.
Check the requirements for constructing a confidence interval for the proportion are satisfied. Show your work. (See the note in the blue box on page 426)
How are confidence intervals affected by sample size?
How does the margin of error for the confidence interval in Part 1 compare to the margin of error for your confidence interval in Part 2? (compute both and compare)
Does the confidence interval you constructed in Part 2 contain the claimed proportion given by Mars Inc?
Do you believe the claims given by Mars Inc?
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The following is a payoff table giving profits for various situations.
States of Nature Alternatives A B C D
Alternative 1 120 140 170 160
Alternative 2 210 130 140 120
Alternative 3 120 140 110 190
Do Nothing 0 0 0 0
a. What decision would a pessimist make?
b. What decision would an optimist make?
c. What decision would be made based on the realism criterion, where the coefficient of realism is 0.60?
d. What decision would be made based on the equally likely criterion?
e. What decision would be made based on the minimax regret criterion? Suppose now that the probabilities of the 4 states of nature are known, that is, the probability to observe A is 30%, the probability to observe B is 35%, the probability to observe C is 20%, and the probability to observe D is 15%. Answer the following
f. What decision would be made based on the expected monetary value?
g. What is the EVPI
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1) Let X be a continuous random variable. What is true about
fX(x)fX(x)?
fX(2) is a probability.
fX(2) is a set.
It can only take values between 0 and 1 as input.
fX(2) is a number.
2) Let X be a continuous random variable. What is true about
FX(x)FX(x)?
FX(x) is a strictly increasing function.
It decreases to zero as x→∞x→∞.
FX(2) is a probability.
FX(x) can be any real number.
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Engineers concerned about a tower's stability have done extensive studies of its increasing tilt. Measurements of the lean of the tower over time provide much useful information. The following table gives measurements for the years 1975 to 1987. The variable "lean" represents the difference between where a point on the tower would be if the tower were straight and where it actually is. The data are coded as tenths of a millimeter in excess of 2.9 meters, so that the 1975 lean, which was 2.9646 meters, appears in the table as 646. Only the last two digits of the year were entered into the computer.
Year | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Lean | 646 | 648 | 660 | 670 | 676 | 691 | 700 | 701 | 717 | 721 | 728 | 745 | 761 |
(a) Plot the data. Consider whether or not the trend in lean
over time appears to be linear. (Do this on paper. Your instructor
may ask you to turn in this graph.)
(b) What is the equation of the least-squares line? (Round your
answers to three decimal places.)
y = + x
What percent of the variation in lean is explained by this line?
(Round your answer to one decimal place.)
%
(c) Give a 99% confidence interval for the average rate of change
(tenths of a millimeter per year) of the lean. (Round your answers
to two decimal places.)
( , )
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Use technology and the given confidence level and sample data to find the confidence interval for the population mean μ. Assume that the population does not exhibit a normal distribution. Weight lost on a diet: 99% confidence n=41 x overbar =4.0 kg s=6.9 kg What is the confidence interval for the population mean μ? ___ kg<μ<___ kg (Round to one decimal place as needed.) Is the confidence interval affected by the fact that the data appear to be from a population that is not normally distributed? A. No, because the population resembles a normal distribution. B. No, because the sample size is large enough. C. Yes, because the population does not exhibit a normal distribution. D. Yes, because the sample size is not large enough.
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Scores on a certain IQ test are known to have a mean of 100. A random sample of 60 students attend a series of coaching classes before taking the test. Let m be the population mean IQ score that would occur if every student took the coaching classes. The classes are successful if m > 100. A test is made of the hypotheses H0: m = 100 vs H1: m > 100.
Consider three possible conclusions:
The classes are successful.
The classes are not successful.
The classes might not be successful.
Answer the following questions:
1.Which of the three conclusions is best if H0 is rejected?
2.Which of the three conclusions is best if H0 is not rejected?
3.Assume that the classes are successful but the conclusion is reached that the classes might not be successful. Which type of error is this?
4.Assume that the classes are not successful. Is it possible to make a Type I error? Explain.
5.Assume that the classes are not successful. Is it possible to make a Type II error? Explain.
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I have draw a random sample of 20 of my neighbors. I ask them their income (What can I say? I'm a nosy neighbor). My sample average (x bar) is $41,000. I want to create a 95% confidence interval around x bar.
My estimated standard deviation is $5,000.
What is the 95% confidence internal for the average income in my neighborhood? $38,652 to $43.347, $38,663 to $43,336, $38,809 to $43,191, or not enough information?
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What are ALL the possible difficulties with with fitting linear regression? Please explain the reasoning.
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Read the essay: The Median Isn’t the Message
by Stephen Jay Gould and answer the following discussion question.
Explain why it is preferable for someone in the better half that the distribution of the survival
variable is right skewed, not left skewed.?
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Minium 150-200 words: Why is a confidence interval better than a point estimate? Provide an example
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1. a. Assume that Data Set A depicts the scores of 10 subjects who received either Treatment 1 or Treatment 2. Calculate a t-test for independent means to determine whether the means are significantly different from each other. In your complete answer, remember to include your t-statistic, critical value, and your decision about whether to reject the null hypothesis. For this question, you should assume that different participants received the two different treatments.
b. Now assume that Data Set A depicts the scores of five subjects who received both Treatment 1 and Treatment 2. Calculate a t-test for dependent means to determine whether the means for the two treatments were significantly different. The correlation between the two treatments is +1.00. In your complete answer, remember to include your t-statistic, critical value, and your decision about whether to reject the null hypothesis. For this question, you should assume that the same participants received each of the two treatments.
Data set A:
Treatment 1 |
Treatment 2 |
45 |
60 |
50 |
70 |
55 |
80 |
60 |
90 |
65 |
100 |
Please provide full and detailed answer, and please do not use excel or other programs, rather just answer using the formulas etc.
Thank you very much! :)
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A researcher conducted an ANOVA (alpha = .05) between 4 groups (G1, G2, G3, G4), with 11 people in each group. The MSBetween was 5.62 and the MSWithin was 2, leading to an F test statistic of 2.81.
Answer the following:
1) What were the hypotheses in statistical notation (2 points)?
2) What is the critical value (1 point)?
3) Make a decision regarding whether to reject H0 and what that means with regard to the group means (3 points).
4) What specifically do the MSBetween and MSWithin represent when the null hypothesis is true and when the null hypothesis is false (2 points)?
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