At Litchfield College of Nursing, 81% of incoming freshmen nursing students are female and 19% are male. Recent records indicate that 60% of the entering female students will graduate with a BSN degree, while 90% of the male students will obtain a BSN degree. If an incoming freshman nursing student is selected at random, find the following probabilities. (Enter your answers to three decimal places.)

(a) P(student will graduate | student is female)


(b) P(student will graduate and student is female)


(c) P(student will graduate | student is male)


(d) P(student will graduate and student is male)


(e) P(student will graduate). Note that those who will graduate are either males who will graduate or females who will graduate.


(f) The events described the phrases "will graduate and is female" and "will graduate, given female" seem to be describing the same students. Why are the probabilities P(will graduate and is female) and P(will graduate | female) different?

The term given refers to the sample space of all students, while the term and refers to restricting the sample space to females only.These probabilities are the same.    This is by chance. These probabilities are typically the same.The term and refers to the sample space of all students, while the term given refers to restricting the sample space to females only.

You have just read an interesting article titled, “High School Students’ Perceptions of Their Peers.” In the article, the researchers asked 2500 Canadian high school students various questions relating to their perceptions of other students. The average perception of student cool, on a coolness scale from 1 (not cool) to 10 (extremely cool), was 5 with a standard deviation of 1 and normally distributed. You have a theory that high school students who regularly skateboard to school will be perceived as cooler than students in the general population. You survey 10 students regarding their perceptions of skateboarder coolness using the same scale as the researchers in the article. Your results are tabled below:

From the information given above, carry out the 5-steps of hypothesis testing outlined in chapter

6 of your text and/or study notes for unit 4. Hint: You have a sample size of 10! So root 10 might

have to come into play! Note: Be sure to end with a conclusion regarding your retention or

rejection of the null hypothesis

At Litchfield College of Nursing, 87% of incoming freshmen nursing students are female and 13% are male. Recent records indicate that 60% of the entering female students will graduate with a BSN degree, while 80% of the male students will obtain a BSN degree. If an incoming freshman nursing student is selected at random, find the following probabilities. (Enter your answers to three decimal places.)

(a) P(student will graduate | student is female)


(b) P(student will graduate and student is female)


(c) P(student will graduate | student is male)


(d) P(student will graduate and student is male)


(e) P(student will graduate). Note that those who will graduate are either males who will graduate or females who will graduate.


(f) The events described the phrases "will graduate and is female" and "will graduate, given female" seem to be describing the same students. Why are the probabilities P(will graduate and is female) and P(will graduate | female) different?

-The term given refers to the sample space of all students, while the term and refers to restricting the sample space to females only.

-The term and refers to the sample space of all students, while the term given refers to restricting the sample space to females only.     

-These probabilities are the same.This is by chance.

-These probabilities are typically the same.

Turn the following into a structured informative abstract.

Metalinguistic awareness contributes to effective writing at university. Writing is a meaning-making process where linguistic, cognitive, social and creative factors are at play. University students need to master the skills of academic writing not only for getting their degree but also for their future career. It is also significant for lecturers to know who our students are, how they think and how we can best assist them. This study examines first-year undergraduate Australian and international engineering students as writers of academic texts in a multicultural setting at the University of Adelaide. A questionnaire and interviews were used to collect data about students’ level of metalinguistic awareness, their attitudes toward, expectations for, assumptions about and motivation for writing. The preliminary results of the research show that students from different cultures initially have different concepts about the academic genres and handle writing with different learning and writing styles, but those with a more developed metalanguage are more confident and motivated. The conclusion can also be drawn that students’ level of motivation for academic writing positively correlates with their opinion about themselves as writers. Following an in-depth multi-dimensional analysis of preliminary research results, some recommendations for writing instruction will also be presented.

1. Ability to taste phenylthiocarbamide (PTC) is mostly determined by the gene PTC. The letters T and t are used here to simplify analysis. TT individuals taste a strong bitter taste; Tt people experience a slightly bitter taste: tt individuals taste nothing. A fifth-grade class of 20 students tastes PTC that has been applied to small pieces of paper, rating the experience as “very yucky” (TT), “I can taste it” (Tt), and “I can’t taste it” (tt). For HW, the students test their parents, with these results:
   1. 1. Of six TT students, four have two TT parent and the remaining two have one each of TT and Tt parents.
      2. Of four Tt students, who have two parents who are Tt, and two have one parent who is TT and one parent who is tt.
      3. Of the 10 students who can’t taste PTC, four have two parents who are also tt, but four students have one parent who is Tt and one who is tt.   The remaining two student have two Tt parents.
   2. Calculate the frequencies of T and t alleles in the two populations (parents and children). Is the Hary-Weinberg Equilibrium maintained.

The following data come from a study designed to investigate drinking problems among college students. In 1983, a group of students were asked whether they had ever driven an automobile while drinking. In 1987, after the legal drinking age was raised, a different group of college students were asked the same question. SHOW EXCEL CODES

Drove While Drinking Year

1983 1987 Total

Yes 1250 991 2241

No 1387 1666 3053

Total 2637 2657 5294

A. Use the chi-square test to evaluate the null hypothesis that population proportions of students who drove while drinking are the same in the two calendar years.

B. What do you conclude about the behavior of college students?

C. Again test the null hypothesis that the proportions of students who drove while drinking are identical for the two calendar years. This time, use the method based on the normal approximation to the binomial distribution that was presenting in Section 14.6. Do you reach the same conclusion?

D. Construct a 95% confidence interval for the true difference in population proportions.

E. Does the 95% confidence interval contain the value 0? Would you have expected it to?

The presence of student-owned information and communication technologies (smartphones, laptops, tablets, etc.) in today's college classroom creates learning problems when students distract themselves during lectures by texting and using social media. Research on multitasking presents clear evidence that human information processing is insufficient for attending to multiple stimuli and for performing simultaneous tasks.

To collect data on how multitasking with these technologies interferes with the learning process, a carefully-designed study was conducted at a mostly residential large public university in the Northeast United States. Junco, R. In-class multitasking and academic performance. Computers in Human Behavior (2012)

At the beginning of a semester a group of students who were US residents admitted through the regular admissions process and who were taking the same courses were selected based on their high use of social media and the similarities of their college GPA's. The selected students were randomly assigned to one of 2 groups:

group 1 students were told to text and use Facebook during classes in their usual high-frequency manner;

group 2 students were told to refrain from any use of texting and Facebook during classes.

At the conclusion of the semester the semester GPA's of the students were collected. The results are shown in the table below.

IN-CLASS MUTLITASKING STUDY

Frequent Facebook Use and Texting   

x₁ = 2.87

s₁ = 0.67

n₁ = 65

No Facebook Use or Texting

x₂ = 3.16

s₂ = 0.53

n₂ = 65

Do texting and Facebook use during class have a negative affect on GPA? To answer this question perform a hypothesis test with
H₀: μ₁−μ₂ = 0
where μ₁ is the mean semester GPA of all students who text and use Facebook frequently during class and μ₂ is the mean semester GPA of all students who do not text or use Facebook during class.

Question 1. Calculate a 95% confidence interval for μ1−μ2 where μ₁ is the mean semester GPA of all students who text and use Facebook frequently during class and μ₂ is the mean semester GPA of all students who do not text or use Facebook during class.

The College Board provided comparisons of Scholastic Aptitude Test (SAT) scores based on the highest level of education attained by the test taker's parents. A research hypothesis was that students whose parents had attained a higher level of education would on average score higher on the SAT. The overall mean SAT math score was 514. SAT math scores for independent samples of students follow. The first sample shows the SAT math test scores for students whose parents are college graduates with a bachelor's degree. The second sample shows the SAT math test scores for students whose parents are high school graduates but do not have a college degree.

(a)

Formulate the hypotheses that can be used to determine whether the sample data support the hypothesis that students show a higher population mean math score on the SAT if their parents attained a higher level of education. (Let μ₁ = population mean verbal score of students whose parents are college graduates with a bachelor's degree and μ₂ = population mean verbal score of students whose parents are high school graduates but do not have a college degree.)

H₀: μ₁ − μ₂ ≤ 0

H_a: μ₁ − μ₂ > 0

H₀: μ₁ − μ₂ ≠ 0

H_a: μ₁ − μ₂ = 0

H₀: μ₁ − μ₂ ≥ 0

H_a: μ₁ − μ₂ < 0

H₀: μ₁ − μ₂ = 0

H_a: μ₁ − μ₂ ≠ 0

H₀: μ₁ − μ₂ < 0

H_a: μ₁ − μ₂ = 0

(b)

What is the point estimate of the difference between the means for the two populations?

(c)

Find the value of the test statistic. (Round your answer to three decimal places.)

Compute the p-value for the hypothesis test. (Round your answer to four decimal places.)

p-value =

(d)

At

α = 0.05,

what is your conclusion?

Do not Reject H₀. There is sufficient evidence to conclude that higher population mean verbal scores are associated with students whose parents are college graduates. Reject H₀. There is insufficient evidence to conclude that higher population mean verbal scores are associated with students whose parents are college graduates.     Reject H₀. There is sufficient evidence to conclude that higher population mean verbal scores are associated with students whose parents are college graduates.Do not reject H₀. There is insufficient evidence to conclude that higher population mean verbal scores are associated with students whose parents are college graduates.

1)

A professor using an open-source introductory statistics book predicts that 60% of the students will purchase a hard copy of the book, 25% will print it out from the web, and 15% will read it online. At the end of the semester she asks her students to complete a survey where they indicate what format of the book they used. Of the 126 students, 71 said they bought a hard copy of the book, 30 said they printed it out from the web, and 25 said they read it online. What would be the appropriate set of hypotheses for testing if the professor's predictions were accurate?

• H0: The actual proportion of students who purchase the hard copy of the book is 60%.

  HA: The actual proportion of students who purchase the hard copy of the book is higher than 60%.

• H0: The actual proportion of students who purchase the hard copy of the book is higher than 60%.

  HA: The actual proportion of students who purchase the hard copy of the book is lower than 60%.

• H0: The distribution of the format of the book used by the students does not follow the professor's predictions. HA: The distribution of the format of the book used by the students follows the professor's predictions.
• H0: The distribution of the format of the book used by the students follows the professor's predictions.

  HA: The distribution of the format of the book used by the students does not follow the professor's predictions.

2)

You are conducting a multinomial hypothesis test (αα = 0.05) for the claim that all 5 categories are equally likely to be selected. Complete the table.

Report all answers accurate to three decimal places. But retain unrounded numbers for future calculations.

What is the chi-square test-statistic for this data? (Report answer accurate to three decimal places, and remember to use the unrounded Pearson residuals in your calculations.)
χ2=χ2=

What are the degrees of freedom for this test?
d.f.=

What is the p-value for this sample? (Report answer accurate to four decimal places.)
p-value =

The p-value is...

• less than (or equal to) αα
• greater than αα

This test statistic leads to a decision to...

• reject the null
• accept the null
• fail to reject the null
• accept the alternative

As such, the final conclusion is that...

• There is sufficient evidence to warrant rejection of the claim that all 5 categories are equally likely to be selected.
• There is not sufficient evidence to warrant rejection of the claim that all 5 categories are equally likely to be selected.
• The sample data support the claim that all 5 categories are equally likely to be selected.
• There is not sufficient sample evidence to support the claim that all 5 categories are equally likely to be selected.

Sleep – College Students (Raw Data, Software Required):
Suppose you perform a study about the hours of sleep that college students get. You know that for all people, the average is about 7.0 hours per night. You randomly select 35 college students and survey them on the number of hours of sleep they get per night. The data is found in the table below. You want to construct a 99% confidence interval for the mean hours of sleep for all college students. You will need software to answer these questions. You should be able to copy the data directly from the table into your software program.