Suppose that you plan to borrow $15,000 student loans to attend a university. You are considering borrowing the loan from XYZ. XYZ offers two options for the repayment of your loan. One is the deferred repayment option and the other is interest repayment option. The APR for the deferred repayment option is 3.75% and the APR for the interest repayment option is 3.15%. You plan to finish your undergraduate study in university within five years. The two repayment options are described as below:Deferred repayment option: You make no scheduled student loan payments for 5 years while you are in school and in 1 year of the grace period after you graduate. However, the unpaid interest every month will be added to your principal amount at the end of your grace period. After the grace period, the total amount your will pay will be equal to the principal you borrow and the accumulated unpaid interest. Each month you will be required to pay the same amount, which includes interest and the required principal repayment. You are required to completely pay off your loan within 10 years. Interest repayment option: You pay interest every month when you are in school and in grace period. After the grace period, you will start to pay the principal of the loan. Each month you will be required to pay the same amount, which includes interest and the required principal repayment. You are required to completely pay off your loan within 10 years.

1. Please use Excel to work on the following questions:

1) Set up the loan amortization tables for the loans with these two different repayment options, respectively.

2) How much interest will you pay in total when you pay off your loan offered by these two different repayment options, respectively?

3) How much will you pay in total, including interest and principal, for these two different repayment options, respectively?

1. A research study examined the blood vitamin D levels of the entire US population of landscape gardeners. The population average level of vitamin D in US landscapers was found to be 45.29 ng/mL with a standard deviation of 4.701 ng/mL. Assuming the true distribution of blood vitamin D levels follows a Gaussian distribution, if you randomly select a landscaper in the US, what is the likelihood that his/her vitamin D level will be between 57.21 and 60.85 ng/mL?

2. Suppose at random 30% of school children develop nausea and vomiting following holiday parties and that you conduct a study to examine this phenomenon, with a sample size of n=43. What is the probability that 31 or more children become sick?
3. A research study examined the blood vitamin D levels of the entire US population of landscape gardeners. The population average level of vitamin D in US landscapers was found to be 54.66 ng/mL with a standard deviation of 5.638 ng/mL. Assuming the true distribution of blood vitamin D levels follows a Gaussian distribution, what is the lower value of the region for which approximately 68% of the data are located within the distribution? Recall the 68-95-99.9% observation discussed in the "Normal Distribution" section of the textbook that is helpful in answering the question.

4. Suppose at random 30% of school children develop nausea and vomiting following holiday parties and that you conduct a study to examine this phenomenon, with a sample size of n=28. What is the probability that between 13 or more and less than 24 children become sick?

5. A research study examined the blood vitamin D levels of the entire US population of landscape gardeners. The population average level of vitamin D in US landscapers was found to be 35.18 ng/mL with a standard deviation of 5.744 ng/mL. Assuming the true distribution of blood vitamin D levels follows a Gaussian distribution, if you randomly select a landscaper in the US, what is the probability that his/her vitamin D level will be between 21.89 and 49.69 ng/mL?

Juliette White is a head of household taxpayer with a daughter named Sabrina. They live at 1009 Olinda Terrace Apt. 5B, Reno, NV 78887. Juliette works at a local law firm, Law Offices of Dane Gray, and attends school in the evenings at Reno Community College (RCC). She is taking some general classes and is not sure what degree she wants to pursue yet. She is taking three units this semester. Full-time status at RCC is nine units. Juliette’s mother watches Sabrina after school and in the evenings (no charge) so that Juliette can work and take classes at RCC. Social security numbers are 412-34-5670 for Juliette and 412-34-5672 for Sabrina. Their birth dates are as follows: Juliette, 10/31/1988; and Sabrina, 3/1/2013.

The Form W-2 Juliette received from the Law Offices of Dane Gray contained the following information:

Juliette also had the following expenses:
                                

Juliette had qualifying health care coverage at all times during the tax year.

Prepare Juliette’s federal tax return. Use Form 1040 and any additional appropriate schedules or forms she may need for credits. For any missing information, make reasonable assumptions. (Input all the values as positive numbers. Instructions can be found on certain cells within the forms. Round your final answers to the nearest whole dollar amount.)

Use the appropriate Tax Tables and EIC table.

I need a 1040, SCH EIC , SCH 8812, 8863

Can you please answer the question

Education reform is one of the most hotly debated subjects on both state and national policy makers’ list of socioeconomic topics. Consider a linear regression model that relates school expenditures and family background to student performance in Massachusetts using 224 school districts. The response variable is the mean score on the MCAS (Massachusetts Comprehensive Assessment System) exam given in May 1998 to 10th graders. Four explanatory variables are used: (1) STR is the student-to-teacher ratio in %, (2) TSAL is the average teacher’s salary in $1,000s, (3) INC is the median household income in $1,000s, and (4) SGL is the percentage of single-parent households. A portion of the data is shown in the accompanying table.

SOURCE: Massachusetts Department of Education and the Census of Population and Housing.

Click here for the Excel Data File

a. For each explanatory variable, discuss whether it is likely to have a positive or negative causal effect on Score.

b-1. Estimate the sample regression equation. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)

b-2. Are the signs of the slope coefficients as expected?

c. What is the predicted score if STR = 18, TSAL = 50, INC = 60, SGL = 5? (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)

d. What is the predicted score if everything else is the same as above except INC = 80? (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.)

Our dataset has the following variables

Commitment- how committed the employee is to the organization [measured on a 5 point Likert scale:-1( strongly disagree= 5(strongly agree); higher number means more committed]

Satisfaction- How satisfied is the employee with his/her job?[ measured on a 5 point Likert scale:- 1 (strongly disagree) to 5 (strongly agree); higher number means more satisfied]

Performance- What was this employee’s rating on his/her last performance appraisal?[ measured on a Likert Scale:- 1 (poor) to 5 (excellent); higher number means higher performance]

Gender- What is the employee’s gender?[Male = 1 Female = 2]

Degree- What is the employee’s highest degree?[ Less than High School = 1 High School = 2 Some College = 3 Bachelor’s Degree = 4 Graduate Degree = 5]

Age- How many years old is the employee? (Years)

Absences- How many absences did this employee have this year? (Number of absent days)

Job- Is the employee management or a line worker? (Management = 1Line Worker = 2)

Self esteem- level of self-esteem [ measured on a 5 point Likert scale:-1 (low) to 5 (high)]

Use the dataset to test whether your employees’ commitment average is significantly different from the national average, which is 3.85 in companies like yours.

i. Is there a statistically significant difference between your company and the national average? [report the t-value and p-value at the end of the sentence stating whether there is a difference: “…end of sentence (t = x.xx, p < 0.xx).”]

ii. How much error is there in your conclusions? [Be sure to write a complete statement using the variable names]

iii. Comment on the practical implication of your findings

Instructions: Choose one of the two options described below. Analyze the data using what you have learned in class.

Instructions: Your answer will include the following:

• A statement of the research question
• A description of the source of the data
• A description of the variables used in the analysis
• A contingency table (two-way table)
• Calculations of relevant percentages
• An answer to the question based on your analysis of the data

Option 1: Cheating

Research questions (do both):

• Are college students willing to report cheating?
• Is the willingness to report cheating related to   gender?

Investigate these questions for the students described in    body_image.xls.

This data comes from a survey of university students at Carnegie Mellon University in Pittsburgh, PA.

Here are the survey questions and associated variables:

Are you a male or a female? Gender (male, female) What is your height in inches? Height (in inches) What is your GPA? GPA

What was your high school GPA?    HS GPA

Where do you tend to sit in class?   Seat (F=front, M=middle, B=back)   How do you feel about your weight? WtFeel (OverWt, AboutRt, UnderWt) Would you report cheating if you witnessed it?    (yes, no)

Option 2: Gender and Body Image

Research question: Do female college students tend to feel differently about their weight compared to male college students?

Investigate this question for the students described in   body_image.xls.

This data comes from a survey of university students at Carnegie Mellon University in Pittsburgh, PA.

Here are the survey questions and associated variables:

Are you a male or a female? Gender (male, female) What is your height in inches? Height (in inches) What is your GPA? GPA

What was your high school GPA?    HS GPA

Where do you tend to sit in class?   Seat (F=front, M=middle, B=back)   How do you feel about your weight? WtFeel (OverWt, AboutRt, UnderWt) Would you report cheating if you witnessed it?    (yes, no)

5. For a random sample of 50 American cities, the linear correlation coefficient between the number of homocides last year and the number of schools in the city was found to be r = 0.653. a. What does this imply?

b. Does this suggest that building more schools in a city could lead to higher levels of homocides? Why or why not?

c. What is a likely lurking variable?

6. The data below are the first exam scores of 10 randomly selected members of a prior stats class and the number of hours they slept the night before the exam.

a. Find the equation of the regression line for the given data. Round the regression line values to the nearest hundredth.

b. What would be the predicted score for a stats student who pulled an all nighter (got 0 hours of sleep) the previous night? Round the predicted score to the nearest whole number.

c. Is this a reasonable question? Explain why or why not.

9. Each year a nationally recognized publication conducts its "Survey of America's Best Graduate and Professional Schools." An academic advisor wants to predict the typical starting salary of a graduate at a top business school using GMAT score of the school as a predictor variable. Total GMAT scores range from 200 to 800. A simple linear regression of SALARY versus GMAT using 25 data points shown below.

Ά0 = -92040 Ά1 = 228 s = 3213 R 2 = 0.66 df = 23 t = 6.67

a) Give a practical interpretation of the estimate of the y-intercept of the least squares line. If none exist explain why.

b) Give a practical interpretation of the slope of the least squares line. If none exists explain why.

c) Give a practical interpretation of R2 = .66

d) Find r

Case study

Rolando Garza is 28 years old, Hispanic, and had partial complex seizure. He is the only child in

a strongly traditional Mexican-American family. The family response to his epilepsy tended

toward overprotective. Since his late teens, Mr. Garza’s family physician has been treating him

with Phenobarbital; yet adequate seizure control has never been achieved.

Mr. Garza seeks vocational rehabilitation services while still suffering from third degree, or deep

partial thickness burns he sustained while working as a chef in a neighborhood restaurant. This is

the second burn he has experienced while at work. Mr. Garza explains that his seizure condition

is disconcerting, but he has more or less become accustomed to it. Seizures occur once every two

to three months.

Mr. Garza is a high school graduate with one year of college. Results of aptitude testing suggest

he has high intelligence. He professes an interest in engineering and completed several years of

architectural drafting coursework while in high school and college. Due to lack of funding, Mr.

Garza states that he was unable to continue his college education.

Presently, Mr. Garza is unsure what to do. He is financially compromised and must leave the

rental home he shares with roommates to move back with his parents. An avid user or his home

computer and the Internet, Mr. Garza believes has developed expertise in this area.

1. What are the issues related to Mr. Garza’s current medical care? What should the referral

sequence be in order to optimize his care?

2. Is Mr. Garza a possible candidate for epilepsy surgery? Explain.

3. Should Mr. Garza attempt to return to his job at the restaurant? Support your response.

4. What are the potential vocational rehabilitation counseling issues related to Mr. Garza’s

situation?

5. Describe cultural considerations relevant to this case and implications of the family’s

overprotective?