Corona Analysis in South Korea 01 DESCRIPTIVE 02 MAPPING 03 ANOVA 04 PREDICTION 05 CONCLUSION AND RECOMMENDATION DESCRIPTIVE “DISTRIBUTION” Based on distribution of Age : 1. Mean of age in deceased about 60 years and majority more than 60 years , and few under 40 years 2. Distribution of the released is normal enough and its mean in 40 years 3. There are two population (majority) in isolated, they are 30 an 60 years 4. The deceased of male isn’t normal and form two distribution, majority in 60 years INFECTION REASON Infection After Visit Number Patients in City STATE by Gender and AGE DESCRIPTIVE “Our goal is to change the wy decisions get made." Female Patient Male Patient Infection reason contact with patient MAPPING Corona in South Korea MAPPING Confirmed Corona MAPPING Death Caused Corona ANOVA It is definitely not only character recognition Interpretation Region Variance Analysis of (Y=count of patient ) The Region Variance isn’t significant to impact the count of patient Corona in Korea Interpretation The Infection Variance isn’t significant to impact the count of patient Corona in Korea Infection Variance of Y (Y=count of patient) ANOVA It is definitely not only character recognition Interpretation The Infection Variance isn’t significant to impact the count of patient Corona in Korea Visit Variance Analysis of Y (Y=count of patient ) ANOVA It is definitely not only character recognition Interpretation There aren’t the impact of interaction from variable to the count of patient Interaction Analysis PREDICTION with Regression (MLP) Graphical Representation of Prediction PREDICTION with Regression (MLP) Graphical Representation of Prediction FORECASTING With ARIMA Gridsearch of tuning ARIMA (p,d,q) With : p_values = [0, 1, 2, 4, 6], d_values =[0, 1, 2, 3] q_values = [0, 1, 2, 4, 6] Best ARIMA Model Graphic ARIMA (1,2,0) Residual Prediction Prediction Residual Relation who causing corona Virus Note : Number is ID
