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Statistics Project
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Business Statistics Project. How the truth or falsehood in the hypothesis

Statistics Project Instructions:

if you make a survey... you must ask all people the same questions. What is your salary. What level of education. Are you planning to continue working in the US? How far would you travel everyday to get a position in your field? How far are you willing to travel if you were to relocate for a position.....

I want to use the salary of graduate students in recent years as a quantitative data measure. In fact, I am considering the salary and benefits of the same diploma in China and the United States. So I am still thinking about it. I also want to explore whether there is a gap between the salary of non-US students and American students from my project.

Statistics Project Sample Content Preview:

Business Statistics Project
Student’s Name
Institutional Affiliation
Business Statistics Project
Introduction
An annual report in November 2016 depicted the state of departures by young people in their quest for education. The number of Americans opting to pursue education is rapidly increasing. Conversely in the USA, the number of international students continues to rise under the rule of President Donald Trump. However, the Institute of International Education provided a funding in 2016 with the US Department of State.
Being the largest sender of its students to the US, China tops the list with over 31.5% as of 2016 enrolled in US campuses. In 2019, over 328,547 students have studied in the country and probably chosen to stay and work while the rest may have returned to their home country. Unfortunately, the recent China-US trade wars may have adversely impacted this number and left the young minds in a dilemma of choice between studying abroad or staying back. The New York University, University of California, Arizona State University, the University of Illinois at Urbana-Champaign, North-eastern University, the University of Southern California and Purdue University are among the top eight institutions that enrolled more than 100,000 international students in 2016.
As for those who choose to study abroad, the number steadily increases each year with over 100,000 in the year 2014-2015. A total of 313,415 students left the country compared the 205,983 in 2004-2005. However, the average study duration programs had shrunk with about 63.1% of the proportion studying abroad doing short summer programs as less eight weeks or lesser. The difference was significant compared to the 51.2% who left a decade earlier (2004-2005). A heated debate ensued as whether to send more students abroad for shorter courses or have a few go for more extended periods. The most substantial figure of those traveling out of the country for education purposes in STEM (Science, Technology, Engineering, and Mathematics) stood at 75,065 followed closely by business students with a 63,015 figure. Moreover, over 66.6% or two-thirds of these students were women. Europe seemed to be the most preferred destination with over 54.5% Americans in UK, Italy, France, Spain and the rest to India, and China.
The wage gap of foreigners who choose to study and stay in the US and Americans is significantly different. A recent study of the same brought to light the situation at the ground for most foreigners. There was no sufficient evidence that the last batch of international students was performing poorly over the period 1980 to 2000. The 1994-2000 arrivals outperformed those in 1980-1986 in terms of earnings growth. Education and experience could not account for much-earning gaps between foreigners and natives. Unfortunately, the 2018 study expresses concerns on current foreigners as they may face more significant challenges in the labor market than the ones in the past did. All these may be attributed to racial and ethnic minorities. The fact alone could explain why many international students may choose to go back to their mother countries after completion of their studies.
In this paper, my research is to determine how the truth or falsehood in the hypothesis: Is there a gap between the salary of Non-US and American students is? Also, I may check the following:
* What is their salary?
* What is your level of education?
* Are you planning to continue working in the US?
* How far would you travel every day to get a job in your field?
* How far are you willing to travel if you were to relocate for a position?
An article by Forbes showing the wage gap between American-born citizens and foreigners depicts a $20,000 difference in annual income. Americans had a median annual income of $59,689, while foreigners had earned $40,145. The latter appeared to be making less money in the 45 states of America. The significant difference may also be attributed to the notion that educated foreigners do not get job opportunities like the natives because they are merely “taking them away from natives.”(See the image below).
My project is the survey of students who stay and work in the US (or Los Angeles) after studying abroad. Categorical and quantitative data will be used and analyzed using Microsoft Excel. Besides, histograms, boxplots, and graphs will be used to display the results of the analysis. Finally, a conclusion will henceforth be found.
Literature Review
In statistics, categorical and quantitative data are common to come across. Seema Singh, a data science aspirant, and journal blogger, descriptively states that to understand the distribution of a particular variable, one must first understand measures used to describe discrete and continuous distributions. Such measures entail:
* Measures of dispersion
* Measures of central tendency
* Measures to define shape of distribution
Measures of dispersion expound on the spread of data or the variation of the quantitative dataset about its primary ratio. Examples of measures of dispersion include range, quartile, interquartile range, variance, and standard deviation. Range is simply the difference between the largest and the smallest value of a dataset. A quartile is any real number that divides a distribution f(x) of a particular random variable into two parts. Usually, there are four quartiles i.e. Q1 for first quartile at 25%, Q2 also mean or the second quartile at 50%, Q3 is the third quartile at 75% and lastly Q4, the fourth quartile of the data at 100% of the data. The interquartile range is equal to Q3-Q1. Half of all values in the data...
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