1. -- 自强不息，厚德载物 -- IE @Applied Statistics, Group Report 1 The Analysis and Forecast of Chinese Population Group Members: 李文华 2009210538 杨丽丹 2009210561 宋 芹 2009210568 杨春晖 2009220200 Instructor: 王凯波

2. IE @Applied Statistics, Group Report 2 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

3. IE @Applied Statistics, Group Report 3 -- 自强不息，厚德载物 -- INTRODUCTION--Background Before 1950 China had demographic characteristics of a pre- modern society with high dead rates and high fertility rates. This situation produced certain stability in population size or, at least, leads to a slow increase. After the foundation of The People’s Republic of China in 1949, China entered its demographic transition: first dead rates began to fall rapidly and second, fertility remained for many years at about an average of six children per woman. As a result of this China experienced rapid population growth due to the high number of children born, a sharp decline of baby dead rate.

4. IE @Applied Statistics, Group Report 4 -- 自强不息，厚德载物 -- INTRODUCTION- INTRODUCTION-China Population Development

5. IE @Applied Statistics, Group Report 5 -- 自强不息，厚德载物 -- INTRODUCTION-China Population Today Now China has a population over 1.3 billion (2007), that is nearly 1/5 the world population. Most of the population are in the east (94%), which are more developed, and enjoying a relatively lower dead rate, and a lower baby dead rate

6. IE @Applied Statistics, Group Report 6 -- 自强不息，厚德载物 -- Our report would like to apply the statistics method with substantial evidence data got from CHINA POPULATION STATISTICS YEARBOOK (1995- 2006), and proceed the research and the analysis on the male-female birth rate, fertility rate and dead rate among different area (city, town, village), and different years, to have a trend analysis and prediction on the total China population. INTRODUCTION--Objective

7. IE @Applied Statistics, Group Report 7 -- 自强不息，厚德载物 -- INTRODUCTION--Terminology City, Town & Village 城市，乡镇，农村 : City and Town in China is administratively defined as statutory cities and statutory towns judging from the population, economic, public finance and Infrastructure four aspects. Village is referred to the areas other than cities and towns. Birth Rate (or crude birth rate) 出生率 :The number of live births per 1,000 population in a given year. Not to be confused with the growth rate. Death Rate (or crude death rate) 死亡率 :The number of deaths per 1,000 population in a given year. Sex Ratio 出生人口性别比 :The number of males per 100 females in a population. Fertility Rate 生育率： The number of live births per 1,000 women ages 15-44 or 15-49 years in a given year. ---- Definition from Administrative Office of the State Council &Population Reference Bureau, USA

8. IE @Applied Statistics, Group Report 8 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

9. IE @Applied Statistics, Group Report 9 -- 自强不息，厚德载物 -- DESCRIPTIVE ANALYSIS-Variables Population size of China: Fertility rate ： ( 生育率 ) ‰ （ 1994-2005 ） Male-female birth rate ： F:100 （ 1994-2005 ） Male (female) ratio of a certain age: % the percentage of the male number of total male population. Death rate: ‰

10. IE @Applied Statistics, Group Report 10 -- 自强不息，厚德载物 -- The data were collected from internet,such as CHINA POPULATION STATISTICS YEARBOOK (1995-2006) ( 中国人口统计年鉴 ) etc. DESCRIPTIVE ANALYSIS-Data Sheet

11. IE @Applied Statistics, Group Report 11 -- 自强不息，厚德载物 -- Observation: Continuous increase since 1962 Increase rate decrease last 20 years DESCRIPTIVE ANALYSIS-Population size

12. IE @Applied Statistics, Group Report 12 -- 自强不息，厚德载物 -- The age distribution of fertility is different. The birth peak for village comes earlier than city. And for all ages the village has higher birth rate. DESCRIPTIVE ANALYSIS- Fertility rate Observation

13. IE @Applied Statistics, Group Report 13 -- 自强不息，厚德载物 -- Jumping town data and stationary city and village data All exceed the rational range (102 to 107) DESCRIPTIVE ANALYSIS- Male/female rate of newborn Observation

14. IE @Applied Statistics, Group Report 14 -- 自强不息，厚德载物 -- Does there are any gender choice? Does female lives longer? DESCRIPTIVE ANALYSIS- Male-Female rate & death rate(2005)

15. IE @Applied Statistics, Group Report 15 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

16. IE @Applied Statistics, Group Report 16 -- 自强不息，厚德载物 --  Data selection ： mainly survey and observation 10 variables 27,000 data points  Data process integrate original data(15 forms) into one form recalculate them to get new data select data points to build a new sample e.g. fertility rate, death rate Male-Female Birth Rate--Data

17. IE @Applied Statistics, Group Report 17 -- 自强不息，厚德载物 -- Main basis of population balance, of great importance. Number of baby boys when 100 baby girls: (year:1994 -2005. type: city, town, village. 36 data points.) One-way ANOVA: Male-female birth rate versus type (city, town and village) Population Balance: Male-Female Birth Rate

18. IE @Applied Statistics, Group Report 18 -- 自强不息，厚德载物 -- Population Balance: Male-Female Birth Rate Conclusions and cause analysis: Three types own significant difference of gender balances and choices. P-value = 0.000<0.05 Boy preference: village (highest)  town  city (lowest) Viewpoint that Man is superior to woman The farm work and lifestyle Education Medical technique (helps sharpen the gender choice)

19. IE @Applied Statistics, Group Report 19 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

20. IE @Applied Statistics, Group Report 20 -- 自强不息，厚德载物 -- Main basis of population balance, of great importance. number of babies per 1000 women from age 15-49: Population replacement: Fertility rate (year:1994 -2005. type: city, town, village. 2520 original points.)

21. IE @Applied Statistics, Group Report 21 -- 自强不息，厚德载物 -- Two-way ANOVA: Fertility rate versus type (city, town and village), year Intersection of type and year Population replacement: Fertility rate Conclusions and cause analysis:  It proves that one-child policy in our country works a lot.  Small rise and fall around 2003 result from the very epidemic SARS around 2003,which reduced the contact and pregnant chances. Both significant! type difference: village> town> city year difference: negative trend

22. IE @Applied Statistics, Group Report 22 -- 自强不息，厚德载物 -- Population replacement: Fertility rate Fertility peak (highest fertility age) versus type, year The age peak is around 24 Fertility peak decreases (city changes most. village most stable) The village peak is the highest Data process year(2001-2005), age( with highest fertility), type (city, town and village) Build up a new sample "fertility peak” Scatter plot of fertility peak

23. IE @Applied Statistics, Group Report 23 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

24. IE @Applied Statistics, Group Report 24 -- 自强不息，厚德载物 -- ANALYSIS of RATIO Step 1: Data collection Take city male ratio for example City male ratio=

25. IE @Applied Statistics, Group Report 25 -- 自强不息，厚德载物 -- Step 2: Descriptive date analysis ANALYSIS of RATIO In city, both male and female ratios are near 0.5. But the difference between male ratio and female ratio is getting larger and larger from town to village. Basically, there are more male than female in society. That is the reason why it is hard for many young men to find “Mrs. Right”.

26. IE @Applied Statistics, Group Report 26 -- 自强不息，厚德载物 -- Step 3 Exploratory date analysis ANALYSIS of RATIO

27. IE @Applied Statistics, Group Report 27 -- 自强不息，厚德载物 -- Conclusion: In city, male ratio is equal to female ratio. But it is larger than female ratio in town and village. The difference between male ratio and female ratio is getting larger and larger from city to village. ANALYSIS of RATIO Step 3 Exploratory date analysis

28. IE @Applied Statistics, Group Report 28 -- 自强不息，厚德载物 -- Step 4 Cause analysis City people Just have one kid Higher education Higher pressures in life Dink family Reason 1 Town and village people More than one kid value the male child only Reason 2 And this phenomenon in village is more serious than that in town, so the difference between male ratio and female ratio in village is larger than that in town. ANALYSIS of RATIO

29. IE @Applied Statistics, Group Report 29 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

30. IE @Applied Statistics, Group Report 30 -- 自强不息，厚德载物 -- ANALYSIS of DEAD RATE Take city male dead rate for example City male dead rate ratio= Step 1: Data collection

31. IE @Applied Statistics, Group Report 31 -- 自强不息，厚德载物 -- Step 2: Descriptive date analysis ANALYSIS of DEAD RATE Observation: male dead rate is higher than female’s. And there is another conclusion that the dead rate is increasing from city to village

32. IE @Applied Statistics, Group Report 32 -- 自强不息，厚德载物 -- Step 3 Exploratory date analysis ANALYSIS of DEAD RATE

33. IE @Applied Statistics, Group Report 33 -- 自强不息，厚德载物 -- Conclusion: Male dead rate is higher than female dead rate Dead rate is increasing from city to village Step 3 Exploratory date analysis ANALYSIS of DEAD RATE

34. IE @Applied Statistics, Group Report 34 -- 自强不息，厚德载物 -- reason Male just have one X chromosome Main labor force in society Bad habit: smoking drinking Accident, crime 1:Male dead rate is higher City Higher education Better living standard Better medical care Better work condition It is increasing from city to village generally speaking, city better than town and village; and town is a little better than village. Step 4 Cause analysis ANALYSIS of DEAD RATE

35. IE @Applied Statistics, Group Report 35 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

36. IE @Applied Statistics, Group Report 36 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT-Guideline The analysis here is based on the population data since the foundation of China, and based on 58 year’s population data we could do trend analysis and prediction in qualitative or quantitative analysis. Trend analysis Linear, exponential, quadratic and S-curve Deviation analysis ARIMA Stationary Model determination based on ACF/PACF Prediction and deviation analysis

37. IE @Applied Statistics, Group Report 37 -- 自强不息，厚德载物 -- Continuous increase and a odd decrease point were observed in annually collected population data. From the Figure, we see the increase rate declined in last 20 years. China’s population has reached 132,129*10 4 (2007), we still face the serious population problem and also aging population problem too. TOTAL POPULATION SIZE PREDICT- Trend object

38. IE @Applied Statistics, Group Report 38 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT- Result of trend analysis Linear, exponential, quadratic and S-curve models were used to analysis the increase features. Parameters estimation is based on OLS methods. 4 results were evaluated in 3 elementary indexes as MAD, MAPE, MSE. The result tells us that S-curve models fits China’s increase sharply then slowly reality.

39. IE @Applied Statistics, Group Report 39 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT-Evaluation of 4 models MethodEquationMAPEMADMSD linearYt = 51011 + 1458*t216333932649 exponential growthYt = 56244.4 * (1.01628**t)4352519641671 quadratic trendYt = 49384 + 1618.1*t - 2.668*t**2214943454107 S-curveYt = (10**6) / (6.07150 +14.0151*(0.961598**t)) 211892225774 Trends analysis’s use is to predict future. So we focus on the most recent regression deviation to evaluate these four models. That means we only take the deviation from 2000~2007. MethodMAPEMSEMAD linear 1.881935442385 exponential groth 6.4808082358344 quadratic trend 1.236029671518 S-curve 0.71144129872 Year20082009201020112012 Population size (unite:1*104) 134975135918136836137731138603

40. IE @Applied Statistics, Group Report 40 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT-ARIMA Description ARIMA is developed by Box and Jenkins in 1970s, and it is a famous model in time serious analysis combined auto regression, moving average and also difference operation to treat unstationary time series data. ARIMA （ p ， d ， q ）, is determined in 3 step: Stationary transfer Model determination Parameters estimation

41. IE @Applied Statistics, Group Report 41 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT-Stationary Test A stationary time series data means the mean of the series does not change with time shift, and standard deviation could be limited in a range. Obvious increase trend was observed, so difference operation is needed to transfer the unstationary series into stationary one. But what is the difference order? “Augmented Dickey-Fuller, ADF” test is used in Matlab to test whether the series has a unit root.

42. IE @Applied Statistics, Group Report 42 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT- One order difference solution P-value is smaller than 0.05, so we reject the null hypothesis. The series does not have unit root. It passes the AFD test and then come into the model determination part.

43. IE @Applied Statistics, Group Report 43 -- 自强不息，厚德载物 -- After determine the difference order of d=1, the ARIMA model turns into ARMA model. Model determination is based on ACF & PACF. ACF has a heavy tail and PACF is bobtail, then it is AR(1) model. So based on Box- Jenkins ARIMA(1,1,0) TOTAL POPULATION SIZE PREDICT- One order difference solution

44. IE @Applied Statistics, Group Report 44 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT- One order difference solution Residual check shows a odd points of “1961”. It is far from the normality line. What shall we do? Transfer? Cut the series? We cut this series and take only 1962~2007.

45. IE @Applied Statistics, Group Report 45 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT- Two order difference solution AFD test? Decision vector H shows the 1962-2007 part is not a stationary series any more. And observation shows a decrease trend. So higher order difference is needed.

46. IE @Applied Statistics, Group Report 46 -- 自强不息，厚德载物 -- TOTAL POPULATION SIZE PREDICT- Two order difference solution ARMA is of p=3, q=1 based on Box-Jenkins method SS = 1114603, MS = 27865.

47. IE @Applied Statistics, Group Report 47 -- 自强不息，厚德载物 -- Population increase can be estimated by above function to get future value based on historical ones. ARIMA Model: C1 Final Estimates of Parameters Type Coef SE Coef T P AR 1 0.9138 0.0714 12.88 0.000 Constant 124.68 31.32 3.37 0.002 Mean 1313.7 390.3 Number of observations: 46 Residuals: SS = 1773508 (backforecasts excluded) MS = 40307 DF = 44 TOTAL POPULATION SIZE PREDICT- Two order difference solution

48. IE @Applied Statistics, Group Report 48 -- 自强不息，厚德载物 -- TOTAL POPULATION-Prediction and Deviation Analysis Future increase and it 95% CI could be predicted, then the total population could be get respectably. MAPE dropped nearly 91%, MSD 99% and MAD 91%. MethodMAPEMSDMAD S-curve 0.71144129872 ARIMA(1,1,0) 0.06605873 Improvement( with S-curve ) 0.9142860.9947050.916284 (2000-2007)

49. IE @Applied Statistics, Group Report 49 -- 自强不息，厚德载物 -- TOTAL POPULATION PREDICT-ARIMA Result Year (unite:1*10 4 ) 20082009201020112012 ARIMA(3,2,1) 132,790133,404134,030134,614135,186 S-curve134,975135,918136,836137,731138,603

50. IE @Applied Statistics, Group Report 50 -- 自强不息，厚德载物 -- OUTLINE PART 1:Introduction (Background, Objective, Terminology ) PART 2:Descriptive Analysis PART 3:Hypothesis Test of Male-Female Birth Rate (Descriptive date, Exploratory date, Cause analysis) PART 4: Fertility Comparison (Descriptive date, Exploratory date, Cause analysis) PART 5:Analysis of Ratio (Descriptive date, Exploratory date, Cause analysis) PART 6:Analysis of Dead Rate (Descriptive date, Exploratory date, Cause analysis) PART 7:Time Series Analysis of Total Population Size (Trend analysis, Model based analysis) PART 8: Conclusion

51. IE @Applied Statistics, Group Report 51 -- 自强不息，厚德载物 -- Features: total population population increase what’s right now? Chinese population takes up nearly 1/4 of the world population. post-80’s has come into the region of birth peak which keeps a relative high population increase. health care improved in large extent and people will have a much longer life. What’s in future? around 2050 China will face a first time population decrease. social problems but also economic challenges will show up. Economy increase? Social welfare? Stability ? Is it necessary for the government to revise the birth control police to keep China’s population and the increase at a reasonable region? TOTAL POPULATION PREDICT-Conclusion

52. IE @Applied Statistics, Group Report 52 -- 自强不息，厚德载物 -- Thanks!