This is my final project presentation of my statistic class. Thanks!

1. Final Presentation
Yuchen Yang
yy3743

2. Self-Introduction
Yuchen Yang comes from Anhui, China. She finished her bachelor
degree in Business Economics at the University of California, Irvine.
Her time on the campus ground of UC Irvine planted the seed of her
curiosity about Marketing. To test her potential in the field of
Marketing, she worked at Overseas Student Service Corp (OSSC)
from August 2018 to December 2019 as a Marketing and Sales
Specialist Intern. The professional setting of OSSC propelled her to
acquire new sets of skills and pools of knowledge. Here, the
marketing campaigns in which she was involved were of more
complexity and based on the Wechat app. Thus, when striving to build
collaborative relations with business partners, she was conscientious
of the potential ramifications on the firm’s revenue and profit.
Because of her experience at OSSC, she became clear of her career
trajectory. She intends to begin accumulating insights by working as a
Marketing professional.
Yuchen(Joyce) Yang
LinkedIn: https://www.linkedin.com/in/yuchen-yang-2b81141b8

3. Class Link:
■ Github link: https://github.com/yy3743
■ Kaggle Link: https://www.kaggle.com/yy3743

4. Summary
From this class, I learned research methods to support prospect, customer and competitive
analyses including how to execute a survey and use syndicated research. Using measures of
central tendency and dispersion, I learned how to develop and assess these statistical
measures to better understand potential data issues prior to analysis.

5. Capstone 2 ( World Happiness Report )
Data Source: https://www.kaggle.com/unsdsn/world-happiness?select=2019.csv
2019 World Happiness Report Data Studio Link: https://datastudio.google.com/reporting/53ccfe7d-da71-4255-
9a24-5c0222d08176

6. Capstone 2 (2019 World Happiness Report )
Abstract:
■ This database is about the world happiness report is a landmark survey of the state of
global happiness. The report continues to gain global recognition as governments,
organizations and civil society increasingly use happiness indicators to inform their
policy-making decisions. Leading experts across fields – economics, psychology, survey
analysis, national statistics, health, public policy and more – describe how measurements
of well-being can be used effectively to assess the progress of nations. The reports
review the state of happiness in the world today and show how the new science of
happiness explains personal and national variations in happiness.
■ In my capstone data 2, I mainly focus on the different countries’ people to see their
average Freedom of choices and their average score of happiness.

7. Regression
■ https://github.com/yy3743/NYU_Integrated_Marketing/blob/main/yy3743_(World's_Ha
ppiness_2019).ipynb
■ https://www.kaggle.com/unsdsn/world-happiness?select=2019.csv

8. Capstone 4 Regression
From those two scatterplot, it is easily to see that social support and Freedom to make life choices are tend to
have linear relationship; total GDP and Freedom to make life choice has no obvious linear relationship.

9. Capstone 4 Regression
Y=B+B1X1+B2X2+e
H0:B1=0, B2=0(α=0.05)
X1: Social support
X2: GDP per capita
Y: Freedom to make life choice
Conclusion:
P1value<0.05, so we can reject
the null hypothesis that Social
support and Freedom to make
life choices are not correlated.
P2value>0.05, so we cannot
reject the null hypothesis that
GDP per capita and Freedom to
make life choice are not
correlated.

10. Capstone 4 Regression
Insight:
From those regression data, we know that the Social support and Freedom to make life
choice are tend to be correlated, and the GDP per capita and the Freedom to make life are
not correlated. In a marketing perspective, people who get social support could influence
their freedom to make life choice. In addition, the GDP per capita has nothing to do with the
people’s freedom to make choice.

11. Capstone 4 Regression
Assumption 4: The variance of the error term is not constant. This variance does not
depend on the values assumed by X. (Unsatisfied)

12. Capstone 4 Regression
Assumption1: The error term is not distributed.
For each fixed value of X, the distribution of Y is
normal. (Unsatisfied)
Assumption3: The mean of the error term is not
0.(Unsatisfied)
P value= 0<0.05

13. Assumption 6: We can reject the null hypothesis that the independent variables in X are not
correlated. This is no issues of multi-collinearity (Satisfied)
P value=0<0.05
Capstone 4 Regression

14. Assumption 5: The error term is uncorrelated. (This is not a time series data.) (satisfied)
Assumption 2: The means of all these normal distributions of Y, given X, lies on a straight line with
slope b. ( Unsatisfied)
Capstone 4 Regression

15. Assumptions Check and Further Research
Due to this data analysis, we only focus on the relationship between Social Support and
GDP per capita with the Freedom to make choices. To research the relationship between
those data with the world’s happiness in 2019. The correlations between social support and
freedom to make choices is not strong. The social support is kind related with the freedom to
make choices. In his data, maybe using regression to analysis is not a very good way since
the correlations is not very strong in every picture. Perhaps, using hypothesis test is better to
analysis it.

16. Appendix
Capstone 2

17. Capstone 2