Binary Logistic Regression Analysis in SPSS

In this video, I have simplified how to perform Binary Logistic Regression Analysis in SPSS, and gave detailed interpretations of the result outputs in table-by-table and block-by-block sequence.

The content of this video is detailed and comprehensive, and the interpretations have been simplified to the grassroots and you are hereby advised to watch this video to the end.
The assumptions your dataset are expected to satisfy in order to make the data tenable for the analysis have been highlighted.

After you have seen this video, you will be able to perform the analysis with your own dataset and be able to make necessary interpretation and decision based on target group.

In my usual way, I have provided the necessary synopsis, which introduced you to the topic, terms and functions associated with Binary Logistic Regression Analysis, especially for those who are new to this kind of regression analysis. So, it is important you patiently see the introduction/synopsis before delving into the analysis proper.

Below is the video timeline provided to enable you move faster based on your area of interest:

TIMELINE:
0:00 – 08:04 Synopsis/Introduction
8:05 – 12:40 Demonstration in SPSS
12:41 – 34:00 Interpretations
34:01 – 34:50 Remarks

If you wish to contact me directly for business purposes, such as Private SPSS Tutorial, or Data Analysis, please use this address to reach me: [email protected]

The following are videos in my channel. Please, click on the links to see the video of your choice.

Convert String to Numeric in Excel Spreadsheet before loading into SPSS:    • String to Numeric in Excel...How?  
Chi-Squared Statistical Test of independence in SPSS:    • Chi-Squared Test in SPSS  
Convert String to Numeric Variable in SPSS (Without Losing Data):    • Convert String to Numeric Variable in SPSS...  
Test of Multicollinearity of Data in SPSS:    • Test of Multicollinearity of Data in SPSS  
Regression Analysis in SPSS Part-2:    • Regression Analysis in SPSS Part 2  
Regression Analysis in SPSS Part-1:    • Regression Analysis in SPSS (Part 1)  
Introduction to SPSS Software for Beginners Part-1:    • Introduction to SPSS Software for Beginner...  
Introduction to SPSS Software for Beginners Part-2:    • Introduction to SPSS Software for Beginner...  
Merge Two Data Files in SPSS (Part-2):   • Merge Two Data Files in SPSS (Part-2)  
Merge Two Data Files in SPSS (Part-1):    • Merge Two Data Files in SPSS (Part 1)  
Introduction to SPSS Software for Beginners (Part-3):    • Introduction to SPSS Software for Beginner...  
Analysis of Variance in SPSS (Effect size and Interpretations):    • Analysis of Variance in SPSS (Effect Size ...  
Test of Normality of Data in SPSS:    • Test of Normality of Data in SPSS  
Identify Outliers using Tukey's Hinges Approach in SPSS:    • Identify Outliers using Tukey's Hinges App...  
Identifying Outliers in Dataset using Stem-and-leaf Plot and Boxplots in SPSS:    • Identify Outliers using Stem-and-leaf Plot...  
Identify Outliers using Scattered Plots in SPSS:    • Identify Outliers using Scattered Plots in...  
How to Perform and Interpret One Sample T-Test in SPSS:    • One Sample T-Test in SPSS and Interpretations  
Paired Sample T-Test in SPSS and Interpretations:    • Paired Sample T Test in SPSS and Interpret...  
How to Perform Descriptive Statistics in SPSS:    • Descriptive Statistics in SPSS  
How to Perform Pearson’s Correlation Analysis:    • How to Perform Pearson's Correlation Analy...  
How to Calculate Pearson’s Correlation Coefficient by Hand, Interpret and Report Results in APA style:    • How to Calculate Pearson's Correlation Coe...  

Titocan Mark Solutions (TMS) is a YouTube Channel that improves the knowledge of how to do things in many endeavours, Please, encourage education and learning by liking and kindly subscribing to this channel, and so that we begin to send you notifications every time I publish new video content. Thank you.

To Subscribe, Please, click on the red SUBSCRIBE button above or on the video to do so.

Thank you.