티스토리챌린지

In a simple linear regression line (LMS), the regression line can be expressed as following equation:y = ax + bwherey = The variable that you want to predict (예측하고 싶은 값) | Dependent variable (종속 변수)x = The variable that you are using to predict (예측에 사용하는 값) | Independent variable (독립 변수)a = Slope (기울기)b = y-intercept (y 절편) 그렇다면, y = ax+b 에서 slope(a)와 y-intercept(b)는 어떻게 구하는지 알아보겠습니다. Recall, r ..

When there are two numerical variables, there are  TrendPositive associationNegative association PatternAny discernible "shape" in the scatterLinear Non-linear Visualize, then quantify  The Correlation Coefficient rMeasures linear association. It is based on the standard units. r is defined as:The average of product of (x in standard units) and (y in standard units) 표준 단위 x와 표준 단위 y의 곱의 평균  In P..