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【Abstract】Based on the statistics of 700 pieces of questionnaires, I find the linear relationship among key factors influencing sleep and sleeping time by using Eviews, the key factors that include working time, degree of education, and gender.
【Key words】sleeping time；working time；degree of education；age；number of kids；gender；least square method
As everyone knows, people spend about one third of their whole life sleeping, which is one of the best way to rest physically and mentally and helps them work and study efficiently after sleeping. However, how do we exactly measure sleep？ In my opinion, sleeping time is the best index to express sleep numerically. Different people could he huge differences in sleeping time. For instance, a painstaking manager working in KPMG may sleep only 6 time everyday, while a little child could spend over 10 time sleeping everyday. This pushes me to find out what on earth determine sleeping time. In Biddle and Hamermesh’s “Sleep and the Allocation of Time” published in 1990, they figured out that sleep consumption has the same essence as other leisure consumption. In other words, one’s choice of work-leisure will influence his or her allocation of sleeping time, which conforms to basic economic instinct. Additionally, based on a series of researches, they also found that people always treat part of their sleeping time as sleeping reserve, like bank reserve, to cope with the changes of economic environment. Statistically, sleeping time is inversely proportional to working time.
My article is based on the research above. Obviously, one’s total working time he tremendous influence on sleep. Besides, other factors, namely degree of education, age, number of kids, and gender, should affect sleeping time as well. As far as I know, an infant has the longest sleeping time, while a mature adult sleeps the least. Therefore, I suppose that the equation of age and sleeping time is like an inverted U curve. All in all, the initial equation is set as
sleep=β0+β1totwrk+β2educ+β3age+β4age2+β5yngkid+β6male+u
Variable Description
sleep total sleeping time at night every week, minutes/week
totwrktotal working time every week, minutes/week
edudegree of education, years
agea
yngkid the number of kids in one’s family, if the number is less
than 3, it stands for 1, and otherwise it stands for 0.
male gender, if one is male, it will stand for 1.
My statistical analysis is based on 700 piecesof questionnaires. According to the initial equation, I use Eviews to get the result based on least square method and find that t-Statistic of coefficient of ,andis not significant, and that the coefficient ofis too all. Therefore, the model needs to be adjusted. Then I try to find the direct relationship betweenand sleeping time. Theand sleeping time are not in the same order of magnitude, so I adjust sleep to log(sleep). However, F-Statistic and t-Statistic of coefficient of is not significant, which means that the number of kids exerts a minute influence on sleep. In a similar way, I find that t-Statistic of coefficient ofis also not significant even in 10% of significant test. Finally, the model is set assleep=β0+β1totwrk+β2educ+β3male+u
The regression result of equation is
（8
All in all, the final conclusions are
1.Sleep is human’s basic physiological need. In other words, everyone needs a least sleeping time, so constant term of the equation is a big figure. However, people may change their sleeping time to he enough time and do other things, like working.
2.In all explanatory variables, working time is the most important factor that affects sleep and has negative relationship with sleep. Obviously, the more time people work, the less time they sleep. Consequently, overworking may cause people to get stuck into enormous pressure and work less efficiently. Therefore, it’s important for us to reasonably allocate the time between working and sleeping.
3.Degree of education is another element that influences sleep and also is inversely proportional to sleeping time. In general, the higher education people receive, the more advanced work they he, which means that they should spend more time finishing their works. It explains the negative link between degree of education and sleep. Of course, people who receive higher education also get higher pays.
4.Gender plays an important role in deciding sleeping time. According to the regression result, male sleeps 91 minutes less than female every week on erage. This is proved by several scientific researches. As everyone knows, compared with female, male is likely to sleep more time physiologically.
【References】 Introductory Econometrics Jeffrey·M·Wooldridge
Wikipediazh.wikipedia.org
[3]Forum of Renming Universitybbs.pinggu.org/
【Key words】sleeping time；working time；degree of education；age；number of kids；gender；least square method
As everyone knows, people spend about one third of their whole life sleeping, which is one of the best way to rest physically and mentally and helps them work and study efficiently after sleeping. However, how do we exactly measure sleep？ In my opinion, sleeping time is the best index to express sleep numerically. Different people could he huge differences in sleeping time. For instance, a painstaking manager working in KPMG may sleep only 6 time everyday, while a little child could spend over 10 time sleeping everyday. This pushes me to find out what on earth determine sleeping time. In Biddle and Hamermesh’s “Sleep and the Allocation of Time” published in 1990, they figured out that sleep consumption has the same essence as other leisure consumption. In other words, one’s choice of work-leisure will influence his or her allocation of sleeping time, which conforms to basic economic instinct. Additionally, based on a series of researches, they also found that people always treat part of their sleeping time as sleeping reserve, like bank reserve, to cope with the changes of economic environment. Statistically, sleeping time is inversely proportional to working time.
My article is based on the research above. Obviously, one’s total working time he tremendous influence on sleep. Besides, other factors, namely degree of education, age, number of kids, and gender, should affect sleeping time as well. As far as I know, an infant has the longest sleeping time, while a mature adult sleeps the least. Therefore, I suppose that the equation of age and sleeping time is like an inverted U curve. All in all, the initial equation is set as
sleep=β0+β1totwrk+β2educ+β3age+β4age2+β5yngkid+β6male+u
Variable Description
sleep total sleeping time at night every week, minutes/week
totwrktotal working time every week, minutes/week
edudegree of education, years
agea
摘自：毕业论文格式下载www.udooo.com
ge, yearsyngkid the number of kids in one’s family, if the number is less
than 3, it stands for 1, and otherwise it stands for 0.
male gender, if one is male, it will stand for 1.
My statistical analysis is based on 700 piecesof questionnaires. According to the initial equation, I use Eviews to get the result based on least square method and find that t-Statistic of coefficient of ,andis not significant, and that the coefficient ofis too all. Therefore, the model needs to be adjusted. Then I try to find the direct relationship betweenand sleeping time. Theand sleeping time are not in the same order of magnitude, so I adjust sleep to log(sleep). However, F-Statistic and t-Statistic of coefficient of is not significant, which means that the number of kids exerts a minute influence on sleep. In a similar way, I find that t-Statistic of coefficient ofis also not significant even in 10% of significant test. Finally, the model is set assleep=β0+β1totwrk+β2educ+β3male+u
The regression result of equation is
（8
1.006）（0.0179） （5.658）（34.274）
What’s more, based on several kinds of tests, the final model doesn’t exist multicollinearity, heteroscedasticity, autocorrelation,源于：查抄袭率怎么发表论文www.udooo.com
and measurement error.All in all, the final conclusions are
1.Sleep is human’s basic physiological need. In other words, everyone needs a least sleeping time, so constant term of the equation is a big figure. However, people may change their sleeping time to he enough time and do other things, like working.
2.In all explanatory variables, working time is the most important factor that affects sleep and has negative relationship with sleep. Obviously, the more time people work, the less time they sleep. Consequently, overworking may cause people to get stuck into enormous pressure and work less efficiently. Therefore, it’s important for us to reasonably allocate the time between working and sleeping.
3.Degree of education is another element that influences sleep and also is inversely proportional to sleeping time. In general, the higher education people receive, the more advanced work they he, which means that they should spend more time finishing their works. It explains the negative link between degree of education and sleep. Of course, people who receive higher education also get higher pays.
4.Gender plays an important role in deciding sleeping time. According to the regression result, male sleeps 91 minutes less than female every week on erage. This is proved by several scientific researches. As everyone knows, compared with female, male is likely to sleep more time physiologically.
【References】 Introductory Econometrics Jeffrey·M·Wooldridge
Wikipediazh.wikipedia.org
[3]Forum of Renming Universitybbs.pinggu.org/