Udemy
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
Development
Web Development Data Science Mobile Development Programming Languages Game Development Database Design & Development Software Testing Software Engineering Development Tools No-Code Development
Business
Entrepreneurship Communications Management Sales Business Strategy Operations Project Management Business Law Business Analytics & Intelligence Human Resources Industry E-Commerce Media Real Estate Other Business
Finance & Accounting
Accounting & Bookkeeping Compliance Cryptocurrency & Blockchain Economics Finance Finance Cert & Exam Prep Financial Modeling & Analysis Investing & Trading Money Management Tools Taxes Other Finance & Accounting
IT & Software
IT Certification Network & Security Hardware Operating Systems Other IT & Software
Office Productivity
Microsoft Apple Google SAP Oracle Other Office Productivity
Personal Development
Personal Transformation Personal Productivity Leadership Career Development Parenting & Relationships Happiness Esoteric Practices Religion & Spirituality Personal Brand Building Creativity Influence Self Esteem & Confidence Stress Management Memory & Study Skills Motivation Other Personal Development
Design
Web Design Graphic Design & Illustration Design Tools User Experience Design Game Design Design Thinking 3D & Animation Fashion Design Architectural Design Interior Design Other Design
Marketing
Digital Marketing Search Engine Optimization Social Media Marketing Branding Marketing Fundamentals Marketing Analytics & Automation Public Relations Advertising Video & Mobile Marketing Content Marketing Growth Hacking Affiliate Marketing Product Marketing Other Marketing
Lifestyle
Arts & Crafts Beauty & Makeup Esoteric Practices Food & Beverage Gaming Home Improvement Pet Care & Training Travel Other Lifestyle
Photography & Video
Digital Photography Photography Portrait Photography Photography Tools Commercial Photography Video Design Other Photography & Video
Health & Fitness
Fitness General Health Sports Nutrition Yoga Mental Health Dieting Self Defense Safety & First Aid Dance Meditation Other Health & Fitness
Music
Instruments Music Production Music Fundamentals Vocal Music Techniques Music Software Other Music
Teaching & Academics
Engineering Humanities Math Science Online Education Social Science Language Teacher Training Test Prep Other Teaching & Academics
AWS Certification Microsoft Certification AWS Certified Solutions Architect - Associate AWS Certified Cloud Practitioner CompTIA A+ Cisco CCNA Amazon AWS CompTIA Security+ Microsoft AZ-900
Graphic Design Photoshop Adobe Illustrator Drawing Digital Painting InDesign Character Design Canva Figure Drawing
Life Coach Training Neuro-Linguistic Programming Personal Development Mindfulness Personal Transformation Life Purpose Meditation CBT Emotional Intelligence
Web Development JavaScript React CSS Angular PHP Node.Js WordPress Vue JS
Google Flutter Android Development iOS Development React Native Swift Dart Programming Language Mobile Development Kotlin SwiftUI
Digital Marketing Google Ads (Adwords) Social Media Marketing Google Ads (AdWords) Certification Marketing Strategy Internet Marketing YouTube Marketing Email Marketing Retargeting
Microsoft Power BI SQL Tableau Business Analysis Data Modeling Business Intelligence MySQL Data Analysis Blockchain
Business Fundamentals Entrepreneurship Fundamentals Business Strategy Business Plan Startup Online Business Freelancing Blogging Home Business
Unity Game Development Fundamentals Unreal Engine C# 3D Game Development C++ 2D Game Development Unreal Engine Blueprints Blender
30-Day Money-Back Guarantee
Business Business Analytics & Intelligence SPSS

SPSS For Research

SPSS data analysis made easy. Become an expert in advanced statistical analysis with SPSS.
Highest Rated
Rating: 4.6 out of 54.6 (1,176 ratings)
27,537 students
Created by Bogdan Anastasiei
Last updated 6/2015
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • perform simple operations with data: define variables, recode variables, create dummy variables, select and weight cases, split files
  • built the most useful charts in SPSS: column charts, line charts, scatterplot charts, boxplot diagrams
  • perform the basic data analysis procedures: Frequencies, Descriptives, Explore, Means, Crosstabs
  • test the hypothesis of normality (with numeric and graphic methods)
  • detect the outliers in a data series (with numeric and graphic methods)
  • transform variables
  • perform the main one-sample analyses: one-sample t test, binomial test, chi square for goodness of fit
  • perform the tests of association: Pearson and Spearman correlation, partial correlation, chi square test for association, loglinear analysis
  • execute the analyses for means comparison: t test, between-subjects ANOVA, repeated measures ANOVA, nonparametric tests (Mann-Whitney, Wilcoxon, Kruskal-Wallis etc.)
  • perform the regression analysis (simple and multiple regression, sequential regression, logistic regression)
  • compute and interpret various tyes of reliability indicators (Cronbach's alpha, Cohen's kappa, Kendall's W)
  • use the data reduction techniques (multidimensional scaling, principal component analysis, correspondence analysis)
  • use the main grouping techniques (cluster analysis, discriminant analysis)
Curated for the Udemy for Business collection

Requirements

  • the SPSS package (version 18 or newer recommended)
  • very basic knowledge of statistics (mean, standard deviation, confidence interval, significance level, things like that)

Description

Become an expert in statistical analysis with the most extended SPSS course at Udemy: 146 video lectures covering about 15 hours of video!

Within a very short time you will master all the essential skills of an SPSS data analyst, from the simplest operations with data to the advanced multivariate techniques like logistic regression, multidimensional scaling or principal component analysis.

The good news – you don't need any previous experience with SPSS. If you know the very basic statistical concepts, that will do.

And you don't need to be a mathematician or a statistician to take this course (neither am I). This course was especially conceived for people who are not professional mathematicians – all the statistical procedures are presented in a simple, straightforward manner, avoiding the technical jargon and the mathematical formulas as much as possible. The formulas are used only when it is absolutely necessary, and they are thoroughly explained.

Are you a student or a PhD candidate? An academic researcher looking to improve your statistical analysis skills? Are you dreaming to get a job in the statistical analysis field some day? Are you simply passionate about quantitative analysis? This course is for you, no doubt about it.

Very important: this is not just an SPSS tutorial. It does not only show you which menu to select or which button to click in order to run some procedure. This is a hands-on statistical analysis course in the proper sense of the word.

For each statistical procedure I provide the following pieces of information:

  • a short, but comprehensive description (so you understand what that technique can do for you)
  • how to perform the procedure in SPSS (live)
  • how to interpret the main output, so you can check your hypotheses and find the answers you need for your research)

The course contains 56 guides, presenting 56 statistical procedures, from the simplest to the most advanced (many similar courses out there don't go far beyond the basics).

The first guides are absolutely free, so you can dive into the course right now, at no risk. And don't forget that you have 30 full days to evaluate it. If you are not happy, you get your money back.

So, what do you have to lose?

Who this course is for:

  • students
  • PhD candidates
  • academic researchers
  • business researchers
  • University teachers
  • anyone looking for a job in the statistical analysis field
  • anyone who is passionate about quantitative research

Course content

14 sections • 149 lectures • 14h 3m total length

  • Preview04:54
  • Preview04:51

  • Preview02:41
  • Preview12:08
  • Preview09:29
  • Preview07:52
  • Preview07:11
  • Preview02:52
  • Preview11:09

  • Preview06:41
  • Preview04:35
  • Preview04:06
  • Preview04:24

  • Preview05:47
  • Preview01:56
  • Preview05:09
  • Preview03:23
  • Guide 16: Crosstabs Procedure
    03:21

  • Guide 17: Checking for Normality - Numerical Methods
    06:34
  • Guide 17: Checking for Normality - Graphical Methods
    03:33
  • Guide 17: Checking for Normality - What to Do If We Do Not Have Normality?
    02:08
  • Guide 18: Detecting Outliers - Graphical Methods
    03:38
  • Guide 18: Detecting Outliers - Numerical Methods
    03:30
  • Guide 18: Detecting Outliers - How to Handle the Outliers
    03:12
  • Guide 19: Data Transformations
    08:52

  • Preview04:08
  • Guide 20: One-Sample T Test - Running the Procedure
    03:17
  • Guide 21: Binomial Test
    04:51
  • Guide 21: Binomial Test with Weighted Data
    03:45
  • Guide 22: Chi Square for Goodness-of-Fit
    05:40
  • Guide 22: Chi Square for Goodness-of-Fit with Weighted Data
    02:43

  • Preview03:56
  • Guide 23: Pearson Correlation - Assumption Checking
    03:58
  • Guide 23: Pearson Correlation - Running the Procedure
    03:23
  • Guide 24: Spearman Correlation - Introduction
    05:12
  • Guide 24: Spearman Correlation - Running the Procedure
    02:43
  • Guide 25: Partial Correlation - Introduction
    05:33
  • Guide 25: Partial Correlation - Practical Example
    03:46
  • Guide 26: Chi Square For Association
    06:36
  • Guide 26: Chi Square For Association with Weighted Data
    03:54
  • Guide 27: Loglinear Analysis - Introduction
    10:19
  • Guide 27: Loglinear Analysis - Hierarchical Loglinear Analysis
    07:30
  • Guide 27: Loglinear Analysis - General Loglinear Analysis
    12:27

  • Preview04:13
  • Guide 28: Independent-Sample T Test - Assumption Testing
    01:36
  • Guide 28: Independent-Sample T Test - Results Interpretation
    05:09
  • Guide 29: Paired-Sample T Test - Introduction
    03:13
  • Guide 29: Paired-Sample T Test - Assumption Testing
    02:50
  • Guide 29: Paired-Sample T Test - Results Interpretation
    02:48
  • Guide 30: One-Way ANOVA - Introduction
    05:17
  • Guide 30: One-Way ANOVA - Assumption Testing
    02:34
  • Guide 30: One-Way ANOVA - F Test Results
    05:04
  • Guide 30: One-Way ANOVA - Multiple Comparisons
    06:47
  • Guide 31: Two-Way ANOVA - Introduction
    07:15
  • Guide 31: Two-Way ANOVA - Assumption Testing
    04:16
  • Guide 31: Two-Way ANOVA - Interaction Effect
    08:46
  • Guide 31: Two-Way ANOVA - Simple Main Effects
    13:14
  • Guide 32: Three-Way ANOVA - Introduction
    09:04
  • Guide 32: Three-Way ANOVA - Assumption Testing
    03:04
  • Guide 32: Three-Way ANOVA - Third Order Interaction
    04:48
  • Guide 32: Three-Way ANOVA - Simple Second Order Interaction
    03:55
  • Guide 32: Three-Way ANOVA - Simple Main Effects
    06:26
  • Guide 32: Three-Way ANOVA - Simple Comparisons (1)
    13:19
  • Guide 32: Three-Way ANOVA - Simple Comparisons (2)
    03:07
  • Preview04:37
  • Guide 33: Multivariate ANOVA - Assumption Checking (1)
    07:34
  • Guide 33: Multivariate ANOVA - Assumption Checking (2)
    04:39
  • Guide 33: Multivariate ANOVA - Result Interpretation
    09:43
  • Guide 34: Analysis of Covariance (ANCOVA) - Introduction
    05:08
  • Guide 34: Analysis of Covariance (ANCOVA) - Assumption Checking (1)
    05:16
  • Guide 34: Analysis of Covariance (ANCOVA) - Assumption Checking (2)
    07:08
  • Guide 34: Analysis of Covariance (ANCOVA) - Results Intepretation
    03:26
  • Guide 35: Repeated Measures ANOVA - Introduction
    03:32
  • Guide 35: Repeated Measures ANOVA - Assumption Checking
    01:52
  • Guide 35: Repeated Measures ANOVA - Results Interpretation
    10:31
  • Guide 36: Within-Within Subjects ANOVA - Introduction
    03:58
  • Guide 36: Within-Within Subjects ANOVA - Assumption Checking
    06:52
  • Guide 36: Within-Within Subjects ANOVA - Interaction
    04:11
  • Guide 36: Within-Within Subjects ANOVA - Simple Main Effects (1)
    07:29
  • Guide 36: Within-Within Subjects ANOVA - Simple Main Effects (2)
    05:01
  • Guide 36: Within-Within Subjects ANOVA - Case of Nonsignificant Interaction
    02:49
  • Guide 37: Mixed ANOVA - Introduction
    03:20
  • Guide 37: Mixed ANOVA - Assumption Checking
    02:45
  • Guide 37: Mixed ANOVA - Interaction
    08:24
  • Guide 37: Mixed ANOVA - Simple Main Effects (1)
    03:50
  • Guide 37: Mixed ANOVA - Simple Main Effects (2)
    06:20
  • Guide 37: Mixed ANOVA - Case of Nonsignificant Interaction
    01:39
  • Guide 38: Mann-Whitney Test - Introduction
    04:04
  • Guide 38: Mann-Whitney Test - Results Interpretation
    06:58
  • Guide 39: Wilcoxon and Sign Tests - Wilcoxon Test
    08:02
  • Guide 39: Wilcoxon and Sign Tests - Sign Test
    02:52
  • Guide 40: Kruskal-Wallis and Median Tests - Kruskal-Wallis Test
    08:29
  • Guide 40: Kruskal-Wallis and Median Tests - Median Test
    03:57
  • Guide 41: Friedman Test
    05:59
  • Guide 42: McNemar Test
    08:13

  • Preview04:29
  • Guide 43: Simple Regression - Assumption Checking (1)
    02:15
  • Guide 43: Simple Regression - Assumption Checking (2)
    07:31
  • Guide 43: Simple Regression - Results Interpretation
    05:04
  • Guide 44: Multiple Regression - Introduction
    02:55
  • Guide 44: Multiple Regression - Assumption Checking
    12:20
  • Guide 44: Multiple Regression - Results Interpretation
    05:01
  • Guide 45: Regression with Dummy Variables
    07:13
  • Guide 46: Sequential Regression
    08:48
  • Guide 47: Binomial Regression - Introduction
    05:16
  • Guide 47: Binomial Regression - Assumption Checking
    02:44
  • Guide 47: Binomial Regression - Goodness-of-Fit Indicators
    08:43
  • Guide 47: Binomial Regression - Coefficient Interpretation (1)
    03:59
  • Guide 47: Binomial Regression - Coefficient Interpretation (2)
    04:03
  • Guide 47: Binomial Regression - Classification Table
    03:42
  • Guide 48: Multinomial Regression - Introduction
    03:41
  • Guide 48: Multinomial Regression - Assumption Checking
    10:53
  • Guide 48: Multinomial Regression - Goodness-of-Fit Indicators
    05:24
  • Guide 48: Multinomial Regression - Coefficient Interpretation (1)
    11:27
  • Guide 48: Multinomial Regression - Coefficient Interpretation (2)
    06:25
  • Guide 48: Multinomial Regression - Coefficient Interpretation (3)
    07:20
  • Guide 48: Multinomial Regression - Classification Table
    03:11
  • Guide 49: Ordinal Regression - Introduction
    07:59
  • Guide 49: Ordinal Regression - Assumption Testing
    06:55
  • Guide 49: Ordinal Regression - Goodness-of-Fit Indicators
    05:03
  • Guide 49: Ordinal Regression - Coefficient Interpretation (1)
    11:19
  • Guide 49: Ordinal Regression - Coefficient Interpretation (2)
    01:26
  • Guide 49: Ordinal Regression - Classification Table
    03:35

  • Guide 50: Reliability Analysis - Cronbach's Alpha
    08:04
  • Guide 50: Reliability Analysis - Cohen's Kappa
    06:05
  • Guide 50: Reliability Analysis - Kendall's W
    04:04
  • Preview04:51
  • Guide 51: Multidimensional Scaling - ALSCAL procedure (1)
    08:32
  • Guide 51: Multidimensional Scaling - ALSCAL procedure (2)
    05:29
  • Guide 51: Multidimensional Scaling - PROXSCAL procedure (1)
    04:28
  • Guide 51: Multidimensional Scaling - PROXSCAL procedure (2)
    04:34

Instructor

Bogdan Anastasiei
University Teacher and Consultant
Bogdan Anastasiei
  • 4.4 Instructor Rating
  • 5,670 Reviews
  • 216,727 Students
  • 12 Courses

      My name is Bogdan Anastasiei and I am an assistant professor at the University of Iasi, Romania, Faculty of Economics and Business Administration. I teach Internet marketing and quantitative methods for business. I am also a business consultant. I have run quantitative risk analyses and feasibility studies for various local businesses and been implied in academic projects on risk analysis and marketing analysis. I have also written courses and articles on Internet marketing and online communication techniques. I have 24 years experience in teaching and about 15 years experience in business consulting. 

  • Udemy for Business
  • Teach on Udemy
  • Get the app
  • About us
  • Contact us
  • Careers
  • Blog
  • Help and Support
  • Affiliate
  • Impressum Kontakt
  • Terms
  • Privacy policy
  • Cookie settings
  • Sitemap
  • Featured courses
Udemy
© 2021 Udemy, Inc.