This video demonstrates how to interpret multiple regression output in SPSS. This example includes two predictor variables and one outcome variable. Unstandardized and standardized coefficients are reviewed.
There was a lot of multiple regression in spss videos. but this is the only video that explains this clearly. this helped me a lot. thank you so much. I really appreciate it.
Wow, thank you so much. I have always liked your narcissist videos and was shocked to see you has the first RU-vid result for "How to read coefficients of a regression" to help me with my Grad School paper. Thanks again. :)
Thank you for clarifying the doubts. Kindly help me in understanding how to run multiple regression analysis (hierarchical stepwise) with 2 predictors and 3 criterion/outcome variables
Thanks, as usual, for another great video. Any chance of getting an explanation of adjusting variables by case population, and how to interpret? For example, comparing outputs of preschools with varying enrollment levels.
Do you use JASP at all? If so please upload some videos. Output explained are the most valuable vids! Are you able to show annoted outputs at all or APA write ups for reports?
Thank you for this video. I'm currently doing my dissertation and all of your videos related to the SPSS have helped me a lot. I have one doubt: I have 4 independent variables(Green marketing mix elements) and 1 dependent variable (consumer purchase intention). While performing correlation and regression for all the elements of the green marketing mix and consumer purchase intention together, there is a contradiction for the variable “Green Place” in terms of positive and negative relations. For regression, I followed the "Enter" method. Green Place with consumer purchase intention: r=0.531, p-value=
Hi Dr. Todd! I hope you're still reading comments here. Im really confused about how many interraters should we need if we only have 2 research assistants to do the actual observation to subjects during data collection? Do we need to add a few experts to join the simultaneous interrater observation in the testing of the tool to strengthen the power of my paper, but the additional experts wont be part of the actual data collection. Then my next question is, how many times do we need to do the interrater reliability testing, and do we need to use the same subject for observation or another subject if we are to repeat the interrater reliability testing? Thank you very much Doctor Todd!
Thank you very much! Great video. Can is use multiple regression for any kind of variable combination (e.g. nominal & nominal, nominal & ordinal, etc.)?
Quick question: when explaining the unstandardized beta coefficients, one unit change in one IV produces a certain change in the DV when the other IV remains *constant*, correct? And this stems from the estimated multiple regression equation
That's great Dr. thanks so much. Plz i need your help to use regression analysis to find out the impact of fringe benefits on job satisfaction and employee engagement. Plz my dependent variables are employee engagement and job satisfaction. I have 14 questions under E.E, 10 under J.S, AND 15 questions under Fringe benefits. Plz how to use regression analysis in this case to find out the impact of fringe benefits on employee engagement and the impact of fringe benefits on Job satisfaction?. plz i need your help. Thanks Dr
Dear Dr. Grande thank for the helpful video. But I have a question in the interpretation of Career limitation that is the 95% confidence interval includes the null hypothesis of no difference" 1" please elaborate it Thank you !!
Thanks, just want to know if possible to make a video on how to interpret the coefficient table of the longitidunal studies. I mean a predictor at Time 2.
So which of the independent variables is a stronger predictor of the dependent variable ? Do we report the negative which has higher Std. coefficients or we report the positive one because it is positive ?
Thank you for all of your video, really helpful, i have a question , in my analysis the constant is not significant but some variable are ,so what does it mean?
Thank you so much for this lecture one more thing I want to ask that is it necessary for all predicted values to have same units?? I mean if two independent variables have same units as the dependent variable but one independent variable have different unit then can we perform the multiple regression analysis??
Thanks for the video! I just have a quick question. My Dependent variable only has values of 1 or 2. Would I still be able to this in the same way or should I use dummy variables?
if I code nominal data into numeric for example 1. NY 2. Tokyo 3. Paris; then can it be used in multiple linear regression?? and if I can how to interpret the result?
If the p value for the model as a whole is not significant but one the indeoendent variable is significant, can I still report the results of that independent variable?
Hello. I have a monitoring dataset with over 6 independent variables which are all categorical and contain partially up to 10 different levels. I'd like to perform a multiple linear regression and suppose that I have to create dummy variables, correct? But that in turn would lead to up to 10 different columns for each independent variable and in consequence, I could not check the overall contribution of each variable itself. I am using SPSS and don't know how to overcome this obstacle. Thanks in advance for your help.
Hello Dr. Grande, your videos are great. I have a more specific question though. I have 7 different Likert scales consisting of several Likert items. The scales are about different concepts and measuring consumers attitudes or behavior. I checked for Cronbach's alpha, and all scales are above .70. So I can compute new variables. Should I use the median or mode when computing new variables? My other question is, is it okay to do multiple regression analysis where one scale is the dependent variable and the rest independent?
How exact can I predict the days when I know the limitations and experience of a person? An outcome of 88,345 days would be to exact I would think, because of the standard errors. How would I make this prediction?
Hello sir ..if in multiple regression linearity assumption cannot full fill after transformation and RSaqure is 0.245 in model fit what to do ? Is multiple regression is applicable still? If not which of analysis is applicable kindly help me out
Hi sir it is an urgent question I have a linear model in this form' y=b0+ b1 C+b2 P+ b3 CP I know who to create linear regression model for the above but my question about the addition of the fourth term can I consider this as an independent variable similar to C and P and then compute CP. Is that possible or not, please?
Hi.. I have a doubt.. in this video.. the coefficient table, the first predictor p value is 0.09 rite.. if the alpha value is 0.05. Then, p value > alpha value.. it should be insignificant right... Please explain
I have found a significant value in the ANOVA table (0.024) but not any significant values in the coefficients table (0.054 and 0.132) what does this say?
this means a relationship does exist (because anova has a p value less than .05 means that the regression line is not linear/ not zero). the coefficient value tells the amount of relationship. this means there is a relationship between your variables but that is very weak. 0.5% and 13%
Why do we take the P value from the significance in the Coefficient table, and not from the significance between our IV and DV's in the correlation table?
T value tells you more or less the same as the P value. But Higher T value is better, meanwhile lower P values are better. So a High T value equals a low P value. As well as a High Std.Error vil reflect itself in a low T value and a high Significance ( as in Worse).