Today, the waves are crashing onto the beach every 5.8 seconds.
The times from when a person arrives at the shoreline until a
crashing wave is observed follows a Uniform distribution from 0 to
5.8 seconds. Round to 4 decimal places where
possible.
1)The probability that wave will crash onto the beach exactly 1.5
seconds after the person arrives is P(x = 1.5) = The probability
that it will take longer than 4.06 seconds for the wave to crash
onto the beach after the person arrives is P(x > 4.06) =
2)Suppose that the person has already been standing at the shoreline for 0.7 seconds without a wave crashing in. Find the probability that it will take between 2.9 and 5.4 seconds for the wave to crash onto the shoreline. ________
3)62% of the time a person will wait at least how long before the wave crashes in? ___________seconds.
4)Find the minimum for the lower quartile. _____________ seconds.
In: Math
The authors of a paper studied a random sample of 351 Twitter users. For each Twitter user in the sample, the tweets sent during a particular time period were analyzed and the Twitter user was classified into one of the following categories based on the type of messages they usually sent.
| Category | Description |
|---|---|
| IS | Information sharing |
| OC | Opinions and complaints |
| RT | Random thoughts |
| ME | Me now (what I am doing now) |
| O | Other |
The accompanying table gives the observed counts for the five categories (approximate values read from a graph in the paper).
| Twitter Type | IS | OC | RT | ME | O |
|---|---|---|---|---|---|
| Observed count | 53 | 60 | 66 | 99 | 73 |
Carry out a hypothesis test to determine if there is convincing evidence that the proportions of Twitter users falling into each of the five categories are not all the same. Use a significance level of
α = 0.05.
(Hint: See Example 14.3.)
Let p1, p2, p3, p4, and p5 be the proportions of Twitter users falling into the five categories.
State the appropriate null and alternative hypotheses.
H0: p1 =
p2 = p3 =
p4 = p5 = 0.5
Ha: H0 is not
true. H0: p1 =
p2 = p3 =
p4 = p5 = 351
Ha: H0 is not
true. H0:
p1 = p2 =
p3 = p4 =
p5 = 0.2
Ha: H0 is not
true. H0: p1 =
p2 = p3 =
p4 = p5 = 70
Ha: H0 is not
true. H0: p1 =
p2 = p3 =
p4 = p5 = 0.05
Ha: H0 is not
true.
Find the test statistic and P-value. (Use technology. Round your test statistic to three decimal places and your P-value to four decimal places.)
X2 = P-value =
State the conclusion in the problem context.
Do not reject H0. There is not convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same. Reject H0. There is not convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same. Reject H0. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same. Do not reject H0. There is convincing evidence to conclude that the proportions of Twitter users falling into the five categories are not all the same.
In: Math
Mr Ahuja have always been interested in whether or not where a student sits is related to the students overall grades in school. Below is a table that divides students into 3 seating areas: Front, Middle, and Back with their given GPAS.
Front Middle Back
3.062 2.859 2.583
3.894 2.639 2.653
2.966 3.634 3.09
3.575 3.564 3.06
4 2.115 2.463
2.69 3.08 2.598
3.523 2.937 2.879
3.332 3.091 2.926
3.885 2.655 3.221
3.559 2.526 2.646
Calculate a One-Way ANOVA table (using EXCEL) for the data above. Complete the following: At α = .05, test to see if there is a significant difference among the average GPA of all the students based on three areas of seating. Use both the critical and p-value approaches. Include hypotheses, critical values, results, and conclusions in the language of the problem.
In: Math
Q1. Does an average box of cereal contain 368 grams of cereal? A random sample of 36 boxes had a mean of 372.5 and a standard deviation of 12 grams. Test at the .05 level of significance.
In: Math
In: Math
A box contains three white balls, two black balls, and one red ball. Three balls are drawn at random without replacement. Let Y1 be the number of white balls drawn, and Y2 the number of black balls drawn. Find the distribution of Z = Y1 × Y2
In: Math
1. An investigator wishes to compare the average time to relief of headache pain under three
distinct medications, call them Drugs A, B, and C. Fifteen patients who suffer from chronic
headaches are randomly selected for the investigation, and five subjects are randomly assigned
to each treatment. The following data reflect times to relief (in minutes) after taking the
assigned drug.
Test if there is a significant difference in the mean times among three treatments. Use α =
0.05. (apply ANOVA)
| Drug A | Drug B | Drug C |
| 30 | 25 | 15 |
| 35 | 21 | 20 |
| 40 | 30 | 25 |
| 25 | 25 | 22 |
| 35 | 30 | 24 |
a) State the null and alternative hypothesis.
Null: all means are equal
Alternative: Atleast one mean is different
b) State your conclusion about the hypothesis based on the test statistic and critical value
Reject the hypothesis because there is a huge difference between the 3 treatments and their means
c) Perform multiple comparison test to show whether there are significant differences between the drugs
In: Math
For the following data (a) display the data in a scatter plot, (b) calculate the correlation coefficient r, and (c) make a conclusion about the type of correlation. The ages (in years) of 6 children and the number of words in their vocabulary Age, x 1 2 3 4 5 6
Vocabulary size, y 150 1100 1150 1800 2050 2700
A] The correlation coefficient r is
In: Math
A private college report contains these statistics:
75% of incoming freshmen attended public schools.
65% of public school students who enroll as freshmen eventually graduate.
80% of other freshmen eventually graduate.
What percent of students who graduate from the college attended a public high school?
___ % of students who graduate attended a public high school.
(Round to two decimal places as needed.)
In: Math
2. The Dean of Students at the University of Waterloo wanted to
estimate the proportion of students who are willing to report
cheating by fellow students. So, her staff surveyed the 172
students currently enrolled in the introduction to biology class.
The students were asked, “Imagine that you witness two students
cheating on a quiz. Would you tell the professor?” 19 of the
surveyed students responded “yes.” (11 points total)
a. Using these data, calculate the 90% confidence interval for the
proportion of all students at the University of Waterloo that would
report cheating. (4 points)
b. Interpret the confidence interval from part “a” in a sentence.
Interpret in terms of percentages, rather than proportions. (4
points)
c. Is it appropriate to use these data to estimate the proportion
of all students at the university that would report cheating? Why
or why not? (3 points)
In: Math
You don't need to be rich to buy a few shares in a mutual fund.
The question is, how reliable are mutual funds as
investments? This depends on the type of fund you buy. The
following data are based on information taken from a mutual fund
guide available in most libraries.
A random sample of percentage annual returns for mutual funds
holding stocks in aggressive-growth small companies is shown
below.
| -1.6 | 14.6 | 41.7 | 17.3 | -16.9 | 4.4 | 32.6 | -7.3 | 16.2 | 2.8 | 34.3 |
| -10.6 | 8.4 | -7.0 | -2.3 | -18.5 | 25.0 | -9.8 | -7.8 | -24.6 | 22.8 |
Use a calculator to verify that s2 ≈ 349.621
for the sample of aggressive-growth small company funds.
Another random sample of percentage annual returns for mutual funds
holding value (i.e., market underpriced) stocks in large companies
is shown below.
| 16.5 | 0.4 | 7.1 | -1.1 | -3.2 | 19.4 | -2.5 | 15.9 | 32.6 | 22.1 | 3.4 |
| -0.5 | -8.3 | 25.8 | -4.1 | 14.6 | 6.5 | 18.0 | 21.0 | 0.2 | -1.6 |
Use a calculator to verify that s2 ≈ 136.311
for value stocks in large companies.
Test the claim that the population variance for mutual funds
holding aggressive-growth in small companies is larger than the
population variance for mutual funds holding value stocks in large
companies. Use a 5% level of significance. How could your test
conclusion relate to the question of reliability of
returns for each type of mutual fund?
(a) What is the level of significance?
State the null and alternate hypotheses.
Ho: σ12 = σ22; H1: σ12 > σ22Ho: σ12 > σ22; H1: σ12 = σ22 Ho: σ22 = σ12; H1: σ22 > σ12Ho: σ12 = σ22; H1: σ12 ≠ σ22
(b) Find the value of the sample F statistic. (Use 2
decimal places.)
What are the degrees of freedom?
| dfN | |
| dfD |
What assumptions are you making about the original distribution?
The populations follow independent normal distributions.The populations follow dependent normal distributions. We have random samples from each population. The populations follow independent normal distributions. We have random samples from each population.The populations follow independent chi-square distributions. We have random samples from each population.
(c) Find or estimate the P-value of the sample test
statistic. (Use 4 decimal places.)
p-value > 0.1000.050 < p-value < 0.100 0.025 < p-value < 0.0500.010 < p-value < 0.0250.001 < p-value < 0.010p-value < 0.001
(d) Based on your answers in parts (a) to (c), will you reject or
fail to reject the null hypothesis?
At the α = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant.At the α = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant. At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant.At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are statistically significant.
(e) Interpret your conclusion in the context of the
application.
Fail to reject the null hypothesis, there is sufficient evidence that the variance in percentage annual returns for mutual funds is greater in the aggressive-growth in small companies.
Reject the null hypothesis, there is insufficient evidence that the variance in percentage annual returns for mutual funds is greater in the aggressive-growth in small companies.
Reject the null hypothesis, there is sufficient evidence that the variance in percentage annual returns for mutual funds is greater in the aggressive-growth in small companies.
Fail to reject the null hypothesis, there is insufficient evidence that the variance in percentage annual returns for mutual funds is greater in the aggressive-growth in small companies.
In: Math
The director of the Wisconsin Department of Business Licensing is looking for ways to improve employee productivity. Specifically, she would like to see an improvement in the percentage of applications that employees process correctly. The director randomly selects 50 employees and gather data on the percentage of applications each one correctly processed last month. On the recommendation of a consultant, the director has these 50 employees complete a 3-day workshop on Proactive Synergy Restructuring Techniques. At the end of the month following the training, the director collects the application processing data for the same 50 employees.
Help the director analyze these data by conducting a hypothesis test. From a statistical point of view, what can you tell the director?
| employee | score1 | score2 |
| 1 | 93 | 91 |
| 2 | 94 | 96 |
| 3 | 98 | 100 |
| 4 | 94 | 96 |
| 5 | 92 | 94 |
| 6 | 95 | 97 |
| 7 | 98 | 100 |
| 8 | 96 | 98 |
| 9 | 94 | 96 |
| 10 | 98 | 100 |
| 11 | 96 | 98 |
| 12 | 91 | 93 |
| 13 | 96 | 98 |
| 14 | 94 | 97 |
| 15 | 92 | 90 |
| 16 | 98 | 100 |
| 17 | 97 | 99 |
| 18 | 96 | 98 |
| 19 | 98 | 99 |
| 20 | 90 | 92 |
| 21 | 96 | 95 |
| 22 | 90 | 92 |
| 23 | 90 | 93 |
| 24 | 94 | 96 |
| 25 | 98 | 96 |
| 26 | 96 | 98 |
| 27 | 92 | 94 |
| 28 | 96 | 93 |
| 29 | 92 | 94 |
| 30 | 96 | 94 |
| 31 | 95 | 97 |
| 32 | 90 | 92 |
| 33 | 96 | 98 |
| 34 | 96 | 98 |
| 35 | 94 | 95 |
| 36 | 96 | 98 |
| 37 | 94 | 96 |
| 38 | 98 | 97 |
| 39 | 93 | 95 |
| 40 | 97 | 99 |
| 41 | 92 | 91 |
| 42 | 95 | 97 |
| 43 | 99 | 98 |
| 44 | 91 | 93 |
| 45 | 93 | 95 |
| 46 | 95 | 97 |
| 47 | 92 | 95 |
| 48 | 96 | 98 |
| 49 | 93 | 95 |
| 50 | 97 | 98 |
In: Math
The semester average grade for a statistics course is 76 with a standard deviation of 5.5. Assume that stats grades have a bell-shaped distribution and use the empirical rule to answer the following questions (explain your responses with the help of a graph):
1. What is the probability of a student’s stat grade being greater than 87?
2. What percentage of students has stat grades between 70.5 and 81.5?
3. What percentage of students has stat grades between 70.5 and 65?
4. What is the probability of a student’s stat grade being greater than the mean?
In: Math
Questions 15 –17
Personal incomes in a city have an average of $80,000 and standard deviation of $20,000.
15. The percent of personal incomes over $100,000 is
(a) 0.05 (b) 0.1 (c) 0.1587 (d) 0.1841 (e) Not enough information to calculate.
16. In a random sample of 100 people, the probability that the average income in the sample is over $82,000 is
(a) 0.05 (b) 0.1 (c) 0.1587 (d) 0.1841 (e) Not enough information to calculate.
17. In another random sample of 400 people, the probability that the average income in this sample is at least $3,000 more than the sample average income in Question 16 is
(a) 0.03 (b) 0.05 (c) 0.07 (d) 0.09 (e) Not enough information to calculate.
In: Math
The time needed to complete a final examination in a particular college course is normally distributed with a mean of 100 minutes and a standard deviation of 20 minutes. Answer the following questions.
(a) What is the probability of completing the exam in one hour or less?
(b) What is the probability that a student will complete the exam in more than 60 minutes but less than 75 minutes?
(c) Assume that the class has 90 students and that the examination period is 130 minutes in length. How many students do you expect will be unable to complete the exam in the allotted time?
In: Math