How To Sign New York Banking Presentation

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hi everyone this is lee wong and my net id is lw2988 this is my final presentation of my statistical class this is my contents page so it consists of four main parts the first is self introduction the second is key learning the third is marquee research report and the last is appendix so self introduction i briefly introduce myself so my education background i got my media and cultural bachelor degree on miami university and now i'm studying integrated marketing in new york university and i have two internship experience the first is in hong kong aia and the third is in industry bank that was in china and during i got my internship at aia i learned how to associate with others and how to communicate with my team member and then we got we achieved our goal and from uh the industry bank job i got familiar with bank businesses and i know some like in concerning risk evaluating and individual credit reporting and customer needs mining also i enhanced my communication skills and practical abilities from these internships so here is my linking link github report and cargo notebook links and key learning this is what i learned from this course in this semester i think there are three important things i learned from this course the first is marketing research methodology it find and classify marketing research explain the role in marketing decision making and it target on problem definition the development of approach to the problem the various components of the approach and also we learned data measurements and sampling in this course also i think the most important part from this course is hypothesis testing regulation and customer segmentation it is basic technology techniques of frequency distribution cross tabulation and hypothesis testing also it is the commonly used multivariate tactics of analysis of variance and regulation and here is my market research report the situation is i own them more and i want to understand the customers like who can easily converge so that the sense can be given to marketing team and plan the strategy according through membership cards i got some basic data about my customers like customer id age gender annual income and spending score spending score is something we can assign to the customer based on our defined parameters like customer behavior and purchasing data so the function of regulation model it's x1 i made that was h and x2 a change to annual income and then y value is spending score so after i conducted a linear regression analysis i found that ages affected the spending score but annual income didn't affect that here is my data set and my github so you see this page and you can see some my assumptions and my recreation results and this is my scatter plot i will talk about this later so i want to know whether there is a linear regression relationship between the age and the spending score also between the annual income and the spending scores i made this gap interplayed with the data here so this is my result and i find the x1p value equal to 0 and that was smaller than 0.05 so because we know when p value smaller than 0.05 we conclude that at the second significant level 0.05 we can reject the new hypothesis and the x2p value equals to 0.931 and that was bigger than 0.05 so when p value bigger than 0.05 we conclude that at the significant level 0.05 we can't reject the new hypothesis so through the analysis we can find that ages affected the spending score but the annual income didn't affect the score so we should segment the customer group through differentiating different customer ages and there are two assumptions that are satisfied the first is this one and through this photo we can the screenshot we can find the resid shows is constant so that this assumption is satisfied and this variance is not depending on x assumption value and the second is here and the x residual is normally distributed for the x the distribution of y also is normal so it is satisfied and there is my last part of this presentation appendix this is about my assignments what i did in this semester the first is research design and the data so we got this data and we got a summary this is about an eo company and there is the result then the next assignment hypothesis testing i got executive summary also some links and what i summaried this analysis i got put here and to sample t test pearson's correlation i explained why this test hypothesis and my conclusion also paired t text why this hypothesis and my conclusion also i did power analysis so my conclusion is for a 0.3 effect size power of 0.8 and type i arrow 0.05 we need a sample size of 87 for each group and here is my outside research and plan of future research and the next assignment regression i got exclusive summary i got a logic regression analysis and this is the result and my conclusion and i got all the radio and to analysis and i got conclusion and i how do i evaluate that i use this data to prove my conclusion and the last assignment is customer segmentation i got my executive summary and the data source and some explanations and my cargo link and some data i can prove to improve my finding the k k means clustering finding the best k the album method so based on the research k point zero k equals zero and k means clustering interpreting the clustering so based on this research the customer clustering is a low residency a higher frequency and amount the k means clustering results customers with cholesterol labels equal 1 best fit the criteria also we can see that k means clustering returns 18 target customers and there are my hierarchical clustering and other here radical clustering and based on the rfn criteria the customer clusters with a lower residency a higher frequency and amount from the k-means clustering results we see that customers with clustering labels equal to best fit the crypto rule and that's it there is my presentation of statistical class thank you for watching bye