Which of the following is NOT an assumption on the multiple linear regression mo

Question

Which of the following is NOT an assumption on the multiple linear regression model y = beta_0 + beta_1x_1 + beta_2x_2+...+ beta_kx_k +epsilon? There is no correlation between the dependent variable y and any independent variable x_k, k = 1, 2, ... K. The random errors epsilon_i, j = 1, 2, ..., n, each follows a normal distribution with constant variance for each set of values of the independent variables (x_1, x_2, ... x_K). The random errors epsilon_j, j = 1, 2, ..., n, are independent of each other for different sets of values of the independent variables (x_1, x_2, ... x_K). The independent variables, (x_1, x_2, x_K), are deterministic; hence, they and uncorrelated with each other.

Explanation / Answer

First assumption in the multiple linear regression model is the the indpendent variable and dependent variable has linear relationship. Hence clearely statement (a) is not the correct assumption.

Related Questions

Navigate

• Browse (All)
• Browse W
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.