Thank you for replying. I have two separate data sets. For the first data set the model summary results are: R= .752, R Square=.566, Adjusted R Square=.555 and Std. Error of the Estimate= 9.640.
For the second data set the results are: R= .797, R Square=.635, Adjusted R Square=.623 and Std. Error of the Estimate=8.880.

For both models, I used the same three predictors for one dependent variable (Course Score).

And I have one more question, Should I report the results of checking the linear regression assumptions before start presenting the regression results?

The 2nd model is more appropriate as the value Adjusted R square is more there and even standard error is less. Further, assumption testings you can do. But majorly its practiced for economic data.

Hi, I found this article very helpful. I just have one question about the Model Summary table. What is the acceptable value for “Std. Error of the Estimate”? I am doing research on the factors that influence students’ scores in one subject using three different tests as dependent variables. Thank you in advance. The value I have now is 9.640, is this considered acceptable?

Hi Suad,
There is no specific acceptable value for the standard error of the estimate. Generally the values for significance level, R square or adjusted R square are checked

Varibles entered / removed
Model Varibles entered Varibles
Removed method
1 Event,
Allowance . Enter
a. All requested variables enterd dependent variable: motivation level
b. Depent variable:mdv

interpret ALL the SPSS outputs below as detail as possible Regression Analysis

Model summary
Model r R Square Adjusted R
Square Std Error of the Estimate
1 .669
Allowance ..447 .440 .39184
a. Predictors ( constant, events,allowance

1 month & 3 weeks ago

thank you very much!

it was very clear and helpful

1 month & 2 weeks ago

Thanks Murekatete for appreciation

1 month & 3 weeks ago

Please send me details about regression analysis

1 month & 2 weeks ago

Thank you for replying. I have two separate data sets. For the first data set the model summary results are: R= .752, R Square=.566, Adjusted R Square=.555 and Std. Error of the Estimate= 9.640.

For the second data set the results are: R= .797, R Square=.635, Adjusted R Square=.623 and Std. Error of the Estimate=8.880.

For both models, I used the same three predictors for one dependent variable (Course Score).

And I have one more question, Should I report the results of checking the linear regression assumptions before start presenting the regression results?

Thank you.

1 month & 2 weeks ago

The 2nd model is more appropriate as the value Adjusted R square is more there and even standard error is less. Further, assumption testings you can do. But majorly its practiced for economic data.

2 months & 4 days ago

Hi, I found this article very helpful. I just have one question about the Model Summary table. What is the acceptable value for “Std. Error of the Estimate”? I am doing research on the factors that influence students’ scores in one subject using three different tests as dependent variables. Thank you in advance. The value I have now is 9.640, is this considered acceptable?

1 month & 2 weeks ago

Hi Suad,

There is no specific acceptable value for the standard error of the estimate. Generally the values for significance level, R square or adjusted R square are checked

2 months & 1 week ago

Thank you. This is very helpful

2 months & 3 weeks ago

Thank you. it was very helpful. it was very clear.

3 months & 4 weeks ago

Thanks for this document.

It is simple and clear. it has been very helpful to me. Now I know what to do with my analysis

3 weeks ago

Very satisfying

4 months & 1 week ago

Varibles entered / removed

Model Varibles entered Varibles

Removed method

1 Event,

Allowance . Enter

a. All requested variables enterd dependent variable: motivation level

b. Depent variable:mdv

interpret ALL the SPSS outputs below as detail as possible Regression Analysis

Model summary

Model r R Square Adjusted R

Square Std Error of the Estimate

1 .669

Allowance ..447 .440 .39184

a. Predictors ( constant, events,allowance

4 months & 2 weeks ago

Great post. Thank you

7 months & 2 weeks ago

Source | SS df MS Number of obs = 13

————-+———————————- F(3, 9) = 0.62

Model | 2.47305128 3 .824350427 Prob > F = 0.6188

Residual | 11.9433999 9 1.32704444 R-squared = 0.1715

————-+———————————- Adj R-squared = -0.1046

Total | 14.4164512 12 1.20137094 Root MSE = 1.152

———————————————————————————-

Dperformance | Coef. Std. Err. t P>|t| [95% Conf. Interval]

—————–+—————————————————————-

Dcapitaladequacy | .0011134 .0048725 0.23 0.824 -.0099089 .0121357

Ddeposits | -.0143361 .0113395 -1.26 0.238 -.0399878 .0113155

Dquality | .0224043 .0182389 1.23 0.250 -.0188548 .0636635

soemone help me interpret research variables

11 months & 2 days ago

Thank you! this helps so much.