Other considerations in Regresson Model
1. Qualitative Predictors
예를 들어 신용 데이터는 balance, age, cards, education, income, limit 등과 같은 회원들의 정보들을 포함하고 있다.
이때 gender는 p-value가 높기때문에 상관관계가 별로 없다고 판단된다. 이런것들을 dummy variable이라고 칭한다.
2. Extensions of the Linear model
-Non-linear Relationships
3. Potential Porblems
two of the most important assumptions state that the relationship between the predictors and response are additive and linear.
-Non-linearity of response - predictor relationships.
-correlation of error terms.
-non-onstant variance of error terms.
-outliers
-High-leverage points
-Collinearity
3.4 Marketing plan
1. Is there a relationship between advertising sales and budget?
2. How strong is the relationship?
3. Which media contribute to sales?
4. How large is the effect of each medium on sales?
5. How accurately can we predict future sales?
6. Is the relationship linear?
7. Is there synergy among the advertising media?
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