- CFA Exams
- CFA Level I Exam
- Study Session 2. Quantitative Methods (1)
- Reading 5. Multiple Regression
- Subject 4. The Standard Error of Estimate in Multiple Linear Regression Model

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**CFA Practice Question**

Suppose you want to know whether Fidelity Select Technology Fund (FSTF) behaves more like a large-cap growth fund or a large-cap value fund. You want to estimate the regression Y-hat

_{t}= b_{0}+ b_{1}X_{1t}+ b_{2}X_{2t}+ e_{t}, where Y_{t}is the monthly return to the FSTF, X_{1t}is the monthly return to the S&P 500 Growth Index, and X_{2t}is the monthly return to the S&P 500 Value index. The table below shows the results of a multiple linear regression using monthly data from December 1994 through March 2009.

Calculate the standard error of estimate (SEE) for the regression in the table above.

Correct Answer: From the table we can calculate the standard error of estimate as (0.3682/169)

^{1/2}= 0.0467. Thus the residual standard error is 4.67% a month.###
**User Contributed Comments**
6

User |
Comment |
---|---|

hrai123 |
SEE is really square root of Mean square of residuals in the Anova table |

katybo |
That is right: MSE = SSE / n-k-1 |

MasterD |
Thus SEE = (MSE)^(1/2) = (SSE/(n-k-1))^(1/2) |

mikeb119 |
And according to the previous question: "The standard error of estimate is equal to the standard error of the residual." So you can just pull the 0.0467 from the table. |

Nightsurfer |
mikeb119, I was going to point out the same thing. |

quanttrader |
SEE=sqrt(MSE), MSE provided but can also be calculated as SSE/n-k-1 |