Linear Regression Analysis in SPSS, How to run Regression in SPSS (Lesson 9)

[@atulhadap2176]

Sir, you have a knack of making complex into simple

[@TheConceptsbyDrAtifBilal]

Thank You

[@user-pl7oo6dc3j]

Your videos are amazing! thank you so much.

[@TheConceptsbyDrAtifBilal]

Glad you like them!

[@user-pl7oo6dc3j]

@@TheConceptsbyDrAtifBilal do you have any video about computing two variables into one with do if? A questionnaire with two sub scale measured similarity to two different things. Now the end variables depends on those two. So we can categorize the depended variable in to 4 section. I need to assign 1 or any number to low on two variables (values: )1-174) , low in one and high in the other variable, and high in both. ( 4 sections as the dependent variable) If x is low and y is low, then it’s called a If x is low and y is high, then compute it as b If x is high and y is low, then comput those values to c If both x and y are high, then compute the values as d for those samples. Thanks

[@ivansteenkamp3159]

Thanks for the video - if only I had someone to assist with the data analysis using SPSS. 😂😂😂

[@Yashvishah-ve3fz]

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=

[@TheConceptsbyDrAtifBilal]

One option is that you run separate regression for each IV. Then the values will be ok. Otherwise with multiple regression this will happen. You can simply reject the hypothesis and say that future research should look into this IV for more understanding, or find a reason that in your sample or context it behaves differently

[@Yashvishah-ve3fz]

Okay. Thank you so much. This means a lot.

[@statisticslearning]

Very good

[@TheConceptsbyDrAtifBilal]

Thanks

[@josephineadewole7953]

Thank you so much for this wonderful lecture. Pls is there a way you can make a video on predicting students academic performance using some course in this linear regression. Thank you

[@TheConceptsbyDrAtifBilal]

Thank you, Will try uploading it.

[@mlyeo]

Dr Atip, thank you for sharing this video. I have tried it out. You mentioned that most important is the sig cannot be more than 0.005. What if I got 6 independent variables showing sig with more than 0.005. What does it mean by not significant if sig is more than 0.005? For this case, is that means the 6 independent variables do not link to the dependent variable? Please advice. Thank you.

[@TheConceptsbyDrAtifBilal]

First, it is 0.05... not 0.005... and yes no value is significant, you need to try each IV separately.

[@faizrehman6197]

sir, if we want to analyze relationship between age and knowledge, and knowledge variable has five questions and each question has 5 answers, only one answer is correct, should we have to use simple linear regression or logistic regression and can we covert each questions into new variable as making correct answer as 1 and all incorrect answer as 0 and then adding all 5 answers into new variable for finding the relationship between age and knowledge

[@SUBRATAKUMARMAITI]

good

[@anamrizwan2552]

Dear sir, i am using correlation and regression analysis in my research but the sig. value in correlation is not significant (not less than 0.05) but correlation is positive and also the sig. value of regression analysis next to F-stat is 0.061 which is not significant either. Therefore model is not fit. Shall i carry on with my analysis and accept null hypothesis? or what? can you please help? Also i have done test for normality and skewness and kurtosis, everything is in range and data is normally distributed. your videos are really helpful. Can you please clarify my doubts? I will be really grateful to you. Thanks!

[@TheConceptsbyDrAtifBilal]

You can I crease some sample I am sure things will be ok.

[@nr8791]

Would you plz put the link of SPSS to download !

[@hameemislam753]

@ Dr Atif sir is it necessary to check univariate and multivariate outliers in our data set before going for final analysis

[@TheConceptsbyDrAtifBilal]

If you are using the Liker Scale, then it is not required. Suppose the answers were only from 1 to 5... then there there is no need, but just check if there is any typo.

[@asadnaeem8095]

Dear sir what is the different between unstandardized coefficient beta and standardized coefficient beta? Nd also which value is taken while accepting/rejecting a hypothesis?

[@TheConceptsbyDrAtifBilal]

Unstandardized one

[@fatimaasarfraz928]

What about subscales of one dependent variable and one independent variable?how can we run regression then?

[@TheConceptsbyDrAtifBilal]

If you want to do linear regression, then place all subscales as separate variables in independent variable window and test them separately with each subset of dependent variable. It means all independent variables with one dependent variable at one time.

[@siham432]

What is the best way to import tables from SPSS to the research paper?

[@TheConceptsbyDrAtifBilal]

kzbin.info/www/bejne/f6aZoWqGZ699qassi=BW2q6Xf2fyRJVPcD

[@charlesniromi8609]

sir if i have 2 independent variable and 3 dependent variable how to analyze

[@TheConceptsbyDrAtifBilal]

Put 2 independent variables with each dependent variables. It means you will be running 3 regressions, each time changing your dependent variable.

[@rohitkaushik4916]

Hello Sir, Just Wanted to ask one simple thing that how you have converted a bunch of questions in one category into a single scale?

[@TheConceptsbyDrAtifBilal]

kzbin.info/www/bejne/bZiYep2rnZiUftk