In the analysis the explained sum of squares (SSE) is equal to .346 O 323.70 551.39 O 875.09
In the analysis the explained sum of squares (SSE) is equal to .346 O 323.70 551.39 O 875.09
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
![Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The variables used are:
- **fare**: average price of a one-way fare, in dollars
- **dist**: distance of the flight, in miles
```
. reg lfare ldist
Source | SS df MS Number of obs = 4,596
----------------+---------------------------------- F(1, 4594) = 2696.98
Model | 323.702686 1 323.702686 Prob > F = 0.0000
Residual | 551.391705 4,594 .120024135 R-squared = 0.3699
----------------+---------------------------------- Adj R-squared = 0.3698
Total | 875.094374 4,595 .190444913 Root MSE = .34645
------------------------------------------------------------------------------
| Coef. Std. Err. t P>|t| [95% Conf. Interval]
------------------------------------------------------------------------------
ldist | .4025646 .0077577 51.93 0.000 .3873676 .4177617
_cons | 2.399834 .0521601 46.01 0.000 2.297575 2.502093
------------------------------------------------------------------------------
```
In the analysis, the explained sum of squares (SSE) is equal to __________.
- 0.346
- 323.70
- 551.39
- 875.09
**Explanation:**
The table displays results from a regression analysis where the model attempts to predict the average price of a one-way fare (`lfare`) based on the distance of the flight (`ldist`). The key sections show:
1. **SS (Sum of Squares):**
- **Model SS** (SSE): 323.702686, representing the explained sum of squares, which indicates the variation in the dependent variable explained by the model.
- **Residual SS**: 551.391705, representing the unexplained variation (error) in the model.
- **Total SS**: 875.094374, the total variation in the dependent variable](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa40f37e3-2ab1-45ae-9f9d-501dbb59e515%2F6a8757da-0c9a-400c-8da3-b3de313280f2%2Frzfv8gw_processed.png&w=3840&q=75)
Transcribed Image Text:Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The variables used are:
- **fare**: average price of a one-way fare, in dollars
- **dist**: distance of the flight, in miles
```
. reg lfare ldist
Source | SS df MS Number of obs = 4,596
----------------+---------------------------------- F(1, 4594) = 2696.98
Model | 323.702686 1 323.702686 Prob > F = 0.0000
Residual | 551.391705 4,594 .120024135 R-squared = 0.3699
----------------+---------------------------------- Adj R-squared = 0.3698
Total | 875.094374 4,595 .190444913 Root MSE = .34645
------------------------------------------------------------------------------
| Coef. Std. Err. t P>|t| [95% Conf. Interval]
------------------------------------------------------------------------------
ldist | .4025646 .0077577 51.93 0.000 .3873676 .4177617
_cons | 2.399834 .0521601 46.01 0.000 2.297575 2.502093
------------------------------------------------------------------------------
```
In the analysis, the explained sum of squares (SSE) is equal to __________.
- 0.346
- 323.70
- 551.39
- 875.09
**Explanation:**
The table displays results from a regression analysis where the model attempts to predict the average price of a one-way fare (`lfare`) based on the distance of the flight (`ldist`). The key sections show:
1. **SS (Sum of Squares):**
- **Model SS** (SSE): 323.702686, representing the explained sum of squares, which indicates the variation in the dependent variable explained by the model.
- **Residual SS**: 551.391705, representing the unexplained variation (error) in the model.
- **Total SS**: 875.094374, the total variation in the dependent variable
Expert Solution
Step 1
Given that
SStotal = 875.094374
dfModel = 1 , dfE = 4594
Step by step
Solved in 2 steps
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