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2021-02-12 16:26:44
30-Day Money-Back Guarantee
Teaching & Academics Social Science Logistic Regression

Logistic Regression in SPSS for Social Science Research

Complete step by step guide on logistic regression in SPSS including interpretation and visualization
New
Rating: 4.4 out of 54.4 (2 ratings)
5 students
Created by Zvi Oduba
Last updated 2/2021
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Complete step-by-step guide on how to use logistic regression in your research project, dissertation or thesis
  • See why employers are calling out for students who can use data analysis techniques like regression
  • 👍Understand what logistic regression is, in a way that is easy to understand and not based on statistics or maths
  • 🔎Identify opportunities when looking at datasets to use logistics regression
  • 🧠Learn how to formulate a research question and a hypothesis
  • 👨🏻‍💻Learn how to import, clean and prepare your data in SPSS
  • 📊Build your own logistic regression model in SPSS
  • 📄Interpret and visualise the findings from your model into your research report
  • ✏️Follow along with an over-the-shoulder example
  • 💡Understand odds ratios and p-values
  • 📝Learn how to statistically test hypothesis

Requirements

  • Access to SPSS
  • Good level of written and spoken English
  • Have a keen interest for data analysis and social research
  • Basic knowledge of some statistical concepts would be useful
  • Prior experience of some other quantitative methods and some use of SPSS would be useful

Description

Social research with Logistic Regression in SPSS: A Complete Guide for the Social Sciences

The only course on Udemy that shows you how to perform, interpret and visualize logistic regression in SPSS, using a real world example, using the quantitative research process. Follow along with me as I talk you through everything you need to know to become confident in using regression analysis in your quantitative research report, dissertation or thesis. Perfect for those studying social science subjects or want to increase their statistical confidence and literacy.

What’s in the course?

  • Learn what logistic regression is, why it is so useful and why you should consider using it

  • Start to think critically about research questions, hypothesis, finding a dataset and thinking about variables. Follow along with an over-the-shoulder example

  • Learn how to perform a simple logistic regression in SPSS and how to interpret and visualize the findings

  • Learn how to perform multiple logistic regression in SPSS and make statistical conclusions

Don't fall for other courses that are over-technical, math's based and heavy on statistics! This course cuts all that out and explains in a way that is easy to understand!

Course outcomes

On completion of the course you will fully understand:

  • What logistic regression analysis is and what is used for

  • Learn how to formulate a research question and hypothesis

  • How to independently identify what data sources and variables are suitable for regression analysis

  • Learn how to import and clean your data in SPSS

  • Build your own logistic regression model in SPSS

  • How to interpret the results of a regression output

  • Interpret and visualize the findings from your model into your research report

  • increase your confidence in using quantitative data


    Learn this with a real world social science example, you can follow along with. This is the only course on Udemy that shows you from start to finish how regression analysis can be used in your research report from theory to practice.

Why take this course?

Logistics regression is a statistical model that is used to predict the probability of a certain outcome or event occurring, when that outcome or event is binary (such as pass/fail, true/false, healthy/sick). Logistic regression is used to describe the likelihood of something happening. Social researchers, social science students and academics are increasingly turning to quantitative methods such as logistic regression in their research because, given the right dataset, gives the opportunity to statistically quantify real world social issues.

Regression analysis is used to produce headlines like this:

  • Black people ‘40 times more likely’ to be stopped and searched in UK

  • Schools in poorer areas 4x more likely to have Higher grades downgraded

  • Teens who use e-cigarettes up to 5x time more likely to start smoking

Prospective employers are increasingly looking for students who are experienced in the social sciences but also are confident in data analysis techniques, like logistic regression. The Nuffield Foundation in the UK has highlighted the shortage of quantitatively-skilled social science students in the labour market and has since offered millions of pounds in funding to UK universities in a bid to increase knowledge in quantitative research methods.

Pre-requisites

This course is aimed at students, professionals and beginners in the field who want to begin using the power of logistics regression with SPSS into their study or work. Please don't be scared about statistics, there is NO math's involved in this course. Prior experience of some other quantitative methods and some use of SPSS would be useful, but it is definitely not essential. A passion for data analysis and research will make the process much more enjoyable! Good level of English and access to SPSS is required.



Who this course is for:

  • Undergraduate University students
  • Final year University students
  • Those wanting to increase their level of statistical literacy
  • Those with an interest of using quantitative research methods in social science research

Featured review

M. Reza Roshandel
M. Reza Roshandel
3 courses
2 reviews
Rating: 5.0 out of 53 days ago
This course was enriching for me, not just in the logistic regression but also how to think scientifically and how to put it within a paper. These are major topics lost in many other courses. I am waiting for more from him!

Course content

6 sections • 59 lectures • 4h 24m total length

  • Preview01:01
  • Course Structure
    01:37
  • Preview02:15
  • How to get the most from this course?
    01:52

  • Preview05:22
  • The two types of regression analysis
    02:42
  • Variables in logistic regression
    05:37
  • Examples of logistic regression
    03:09
  • Why is logistic regression so useful?
    02:09
  • The 3 main outputs from a logistic regression
    02:28
  • Understanding Odds Ratios
    02:14
  • Preview01:46
  • Understanding r-squared
    01:54
  • Summarising logistic regression
    01:40
  • Is logistic regression the right type of analysis?
    02:06
  • Recap and sense check of logistic regression
    02:33

  • Introducing the quantitative research process
    02:14
  • Theory
    05:11
  • Preview05:25
  • Using p-value for hypothesis testing
    05:54
  • Research design
    04:16
  • Research questions
    03:15
  • Operationalising concepts
    03:51
  • Finding a secondary dataset
    09:26
  • Evaluating a secondary dataset
    13:37
  • Checking the questionnaire content
    11:50
  • Checking the dataset format
    09:00
  • Recoding text labels to numerical variables
    07:11
  • Univariate analysis
    05:31
  • Correlation vs causality
    03:02
  • Crosstabulation
    03:21
  • Recap of the research process
    05:41

  • Introduction to exploratory analysis in SPSS
    00:52
  • Research example
    12:01
  • Downloading the data
    00:56
  • Navigating SPSS
    05:36
  • Checking variable values and labels
    03:07
  • Descriptive statistics and univariate analysis
    07:53
  • Recoding into binary variables
    10:44
  • Time series analysis
    03:41
  • Crosstabulation and bivariate analysis
    05:02
  • Using the p-value
    03:15
  • Preview02:01

  • Introduction to simple logistic regression
    01:41
  • Reference categories
    02:16
  • Simple logistic regression in SPSS
    01:50
  • Interpreting regression outputs
    10:43
  • Visualising odds ratios
    04:06
  • Summarising the visualisations
    02:57
  • Conclusions
    04:40

  • Introducing Multiple Logistic Regression
    01:45
  • Controlling for other variables
    08:56
  • Finding the control variables
    03:41
  • Model 2
    06:45
  • Model 3
    07:10
  • Model 4
    08:19
  • Model 4 conclusions
    01:43
  • Findings from multiple logistic regression
    03:00
  • Well done!
    00:46

Instructor

Zvi Oduba
Local Government Analyst
Zvi Oduba
  • 4.5 Instructor Rating
  • 2 Reviews
  • 5 Students
  • 1 Course

Hi! I am Zvi Oduba and I have a passion for encouraging more students to use quantitative research methods in the social sciences. I graduated with honours after studying BSocSc graduate in Sociology and Quantitative Research Methods and I am now working as a Local Government Analyst.

I became interested in research methods and statistics at university where I was amazed at how data could be used to answer Sociological lines of enquiry. I decided to do a dissertation exploring the impact of screen time on adolescents' sleep. My dissertation won 'Best Undergraduate Dissertation 2019' winner from The University of Manchester Q-Step Centre.

I have since remained an active Alumni at the University and Q-Step Centre, delivering lecture and seminars to students with the hope to increase their confidence in using data as a social science student and to show them that you do not have to be good at maths to excel in the world of statistics!

I am trained in SPSS, Tableau and Excel.

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