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This Advanced course in SPSS provides higher level skills in SPSS helping students to gain a deeper understanding . It is recommended that students complete the Intro to SPSS Course, found on the NextGenU website, Intro to SPSS , before taking this course if you do not already have a foundational understanding of SPSS. All parts of this training are free, including registration, learning, testing, and a certificate of completion. The course in SPSS is intended for Social Science professionals and academics, healthcare researchers, data analysts, business and management professionals, and anyone interested in learning how to use SPSS.
This Advanced SPSS course was developed by Dr. Marco-Aurelio Hernandez PhD (Biostat), MSc (Stat), MSc(Education), BSc (Bio)
To learn more about the efficacy of online learning and online learning at NextGenU.org please see this article: https://bmcmededuc.biomedcentral.com/articles/10.1186/1472-6920-14-181
This course consists of (5) modules, which include:
Module 1: Introduction to Advanced Data Management Techniques in SPSS
Module 2: Statistical Analysis: Pre-Analysis
Module 3: Statistical Analysis: Regression
Module 4: Statistical Analysis: Parametric Tests
Module 5: Statistical Analysis: Nonparametric TestsThe completion time for this course is estimated at 33 hours 12 minutes, comprising 6 hours and 24 minutes of learning resources, 12 hours and 48 minutes of studying and assimilating the content, and 14 hours of participating in learning activities to assist the learners in synthesizing learning materials.
Upon completing the training (5 modules), you will need to complete a final exam. The final exam will be designed so you have three opportunities to answer correctly until the required score of 70% or higher is obtained.
At the end of each module, there is a learning activity. At the end of the course, after you’ve completed each module, and learning activity, you will have access to a final exam of multiple-choice questions, and a chance to evaluate this course. Once you’ve passed the final exam and completed the course and self evaluations, you will be able to download a certificate of completion from NextGenU.org. We keep all of your personal information confidential, never sell any of your information, and only use anonymized data for research purposes. We are happy to report your testing information and share your work with anyone (your school, employer, etc.) at your request.
Engaging with this Course:
This free course is primarily intended for healthcare researchers, social scientists and academics or anyone who would like to learn more about SPSS techniques, statistical analyses and types of SPSS tests.
Next Steps
Take the short knowledge pre-test below. It allows us to assess various aspects of the course itself.
Complete the registration form.
Begin the course with Module 1: Introduction to Advanced Data Management Techniques in SPSS. In each lesson, read the description, complete all required readings and any required activity, and take the corresponding quizzes.
Disclaimer: This content is designed to enhance your study; we cannot guarantee that the successful completion of these materials will enable you to work in your place of residence as regulations vary by location. If you plan to practice using your new knowledge, to ensure safety and compliance with your local laws, you must successfully complete a program of study approved by the government and relevant local regulatory agencies in your place of practice.
NextGenU.org does not directly confer academic degrees or guarantee that learning institutions will accept NextGenU.org coursework for credit.
To PASS and Obtain a Certificate of completion from NextGenU.org, a learner must successfully complete:
All the reading requirements,
All quizzes and pass with 80% having unlimited attempts,
All activities
The final exam with a minimum of 80% and a maximum of 3 attempts, and
The self and course evaluation forms.
To obtain academic credit towards a degree program
While many learning institutions assign courses or portions of courses from NextGenU.org as part of their students’ learning experience, please be sure to verify that your learning institution will accept NextGenU.org course work as fulfilment or partial fulfilment of learning requirements for your program. NextGenU.org does not directly confer academic degrees or guarantee that learning institutions will accept NextGenU.org coursework for credit.
NextGenU.org is happy to provide your institution with:
a link to and description of the course training, so they can see all its components, including the cosponsoring universities and other professional organization cosponsors;
your grade on the final exam;
your work products (e.g. peer and mentored activities), and any other required or optional shared materials that you produce and authorize to share with them;
your evaluations -- course, self, and peer assessments;
a copy of your certificate of completion, with the cosponsoring universities and other organizations listed.
Take the short knowledge pre-test below. It allows us to assess various aspects of the course itself.
Complete the registration form.
Begin the course with Module 1: Introduction to Advanced Data Management Techniques in SPSS. In each lesson, read the description, complete all required readings and any required activity, and take the corresponding quizzes.
Disclaimer: This content is designed to enhance your study; we cannot guarantee that the successful completion of these materials will enable you to work in your place of residence as regulations vary by location. If you plan to practice using your new knowledge, to ensure safety and compliance with your local laws, you must successfully complete a program of study approved by the government and relevant local regulatory agencies in your place of practice.
NextGenU.org does not directly confer academic degrees or guarantee that learning institutions will accept NextGenU.org coursework for credit.
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Module 1: Introduction to Advanced Data Management Techniques in SPSS
Competency covered in this module:- Data Import Proficiency: Ability to import data from text or comma-delimited files (such as CSV) into SPSS.
- Data Export Proficiency: Skill in exporting SPSS data files to different formats, including Excel, Word, and PDF.
- APA Formatting Skills: Competence in converting SPSS output tables to APA format for academic and professional reporting.
- Data Merging Proficiency: Ability to merge two or more datasets into one cohesive dataset within SPSS.
- SPSS Syntax and Automation:
- Proficiency in using SPSS Syntax to open, save, and reopen files.
- Skills in working with syntax color codes, editing commands, and setting breakpoints to manage and troubleshoot syntax effectively. - Data Visualization Skills: Proficiency in using SPSS Chart Builder to create detailed and meaningful data visualizations.
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Module 1: Lesson 1: Advanced Import/Export Techniques
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Import data stored in a text or comma-delimited file into SPSS.
- Export a data file from from SPSS to Excel, as a Word file and as a PDF file.
- Convert SPSS output tables to APA format.
3 URLs, 2 Files, 1 Assignment, 1 Quiz -
Module 1: Lesson 2: Merging and Appending Datasets
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Merge two or more datasets to form one merged set.
1 URL, 4 Files, 1 Assignment, 1 Quiz -
Module 1: Lesson 3: Introduction to SPSS Syntax
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Use SPSS Syntax to Open, Save and Reopen a file.
- Work with syntax color codes, edit syntax commands, and use breakpoints.
- Work with syntax to recode for missing values, and to collapse qualitative and quantitative categories.
4 URLs, 2 Files, 1 Assignment, 1 Quiz -
Module 1: Lesson 4: Using Chart Builder for Better Charts
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Use SPSS Chart Builder to create more complete data visualizations.
1 URL, 2 Files, 1 Assignment, 1 Quiz -
Module 2: Statistical Analysis: Pre-Analysis
Competency covered in this module:1. Outlier Detection and Data Normality:
- Proficiency in identifying outliers in a dataset using SPSS tools.
- Ability to conduct normality tests on straight numerical (scale) variables and numerical variables grouped by factor variables.
- Skill in creating contingency tables using SPSS for categorical data analysis.
- Proficiency in calculating sensitivity, specificity, probability of false positives and false negatives, Predictive Value Positive (PVP), Predictive Value Negative (PVN), and prevalence using SPSS.
3. Reliability and Validity Testing:
- Expertise in using SPSS tools to measure the reliability and validity of scales and tests, ensuring the accuracy and consistency of data analysis.
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Module 2: Lesson 1: Two Pre-Analysis Procedures
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Identify Outliers in a Dataset with SPSS
- Run normality tests on a straight numerical (scale) variable and a numerical variable that is grouped by a factor variable
2 Files, 2 URLs, 1 Assignment, 1 Quiz -
Module 2: Lesson 2: Contingency Tables and Accuracy Measures
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Create Contingency Tables Using SPSS
- Find Sensitivity, Specificity, the Probability of a false positive, the Probability of a false negative. Predictive Value Positive, Predictive Value Negatiive, and Prevalence with SPSS
2 URLs, 3 Files, 1 Assignment, 1 Quiz -
Module 2: Lesson 3: Reliability and Validity Testing
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Use SPSS tools for Measuring Reliability and Validity
2 URLs, 2 Files, 1 Assignment, 1 Quiz -
Module 3: Statistical Analysis: Regression
Competency covered in this module:1. Simple Linear Regression:
- Proficiency in using SPSS to develop a simple linear regression model for two numerical variables.
- Ability to predict values of the dependent variable based on the given value of the independent variable using the regression model.
2. Multiple Linear Regression:
- Skill in identifying the best multiple linear regression model for one dependent variable and several independent variables using SPSS.
- Competence in testing the model for statistical significance to ensure its reliability.
- Ability to predict values of the dependent variable based on the values of the independent variables that remain significant in the model.
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Module 3: Lesson 1: Simple Linear Regression
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Use SPSS to find a simple linear regression model for two numerical variables, and to predict values of the dependent variable based on the given value of the independent variable.
Click here to start this lesson1 URL, 2 Files, 1 Assignment -
Module 3: Lesson 2: Multiple Linear Regression
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Use SPSS to find the best multiple linear regression model for one dependent and several independent variables
- Test the model for significance
- Predict values of the dependent variable based on the given values of the independent variables that remain in the model.
1 URL, 2 Files, 1 Assignment, 1 Quiz -
Module 4: Statistical Analysis: Parametric Tests
Competency covered in this module:1. One-Sample T-Test:
- Proficiency in testing small and large single samples for statistical significance using the One-Sample T-Test in SPSS.
- Ability to interpret the results of the One-Sample T-Test, understanding its implications on the sample data.
2. Two-Sample T-Test:
- Skill in testing for statistical significance in both independent and dependent samples using the Two-Sample T-Test in SPSS.
- Competence in interpreting the results of the Two-Sample T-Test, differentiating between independent and dependent sample scenarios.
3. Analysis of Variance (ANOVA):
- Proficiency in performing the Analysis of Variance (ANOVA) test to compare means among multiple groups.
- Ability to interpret the ANOVA results to understand differences between group means and their statistical significance.
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Module 4: Lesson 1: One-Sample Tests
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Test Small and Large Single Samples for Statistical Significance with the One-Sample T-Test, Using SPSS
- Interpret the results of the One-Sample T-Test Using SPSS
1 URL, 2 Files, 1 Assignment, 1 Quiz -
Module 4: Lesson 2: Two-Sample Tests and Techniques
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Test Small and Large Single Samples for Statistical Significance with the Two-Sample T-Test for Independent and Dependent Samples, Using SPSS
- Interpret the results of the Two-Sample T-Test Using SPSS
Click here to start this lesson1 URL, 3 Files, 1 Assignment, 1 Quiz -
Module 4: Lesson 3: Analysis of Variance (ANOVA)
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Perform the Analysis of Variance (ANOVA) Test
- Interpret the ANOVA
Click here to start this lesson1 URL, 2 Files, 1 Assignment, 1 Quiz -
Module 5: Statistical Analysis: Nonparametric Tests
Competency covered in this module:1. Nonparametric Testing:
- Proficiency in performing the Mann-Whitney U Test for comparing two independent samples using SPSS.
- Skill in conducting the Kruskal-Wallis Nonparametric ANOVA for comparing more than two independent samples.
- Ability to interpret the results of the Mann-Whitney U and Kruskal-Wallis tests, understanding their significance in nonparametric analysis.
2. Chi-Square Test for Independence:
- Expertise in performing the Chi-Square Test for Independence to assess the association between categorical variables.
- Competence in interpreting the results of the Chi-Square Test to determine the independence or association between variables.
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Module 5: Lesson 1: The Mann-Whitney U Test and the Kruskal-Wallis Test
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Perform the Mann-Whitney Nonparametric Test for Two Samples
- Perform the Kruskal-Wallis Nonparametric ANOVA
- Interpret the Mann-Whitney and the Kruskal-Wallis Tests
1 URL, 2 Files, 1 Assignment, 1 Quiz -
Module 5: Lesson 2: The Chi-Square Test for Independence
Student Learning Outcomes:
Upon completion of this lesson, you will be able to:- Perform the Chi-Square Test for Independence (association of variables)
- Interpret the Chi-Square Test for Independence
1 URL, 2 Files, 1 Assignment, 1 Quiz -
Course and Self Evaluation & Certificate
In this section, you can provide feedback about this course to help us make NextGenU.org better. Once evaluations are completed, you will be able to download your certificate of completion.
