SPSS Beginners: Master SPSS

Learn SPSS Usage and SPSS Statistics
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  • Lectures 48
  • Length 7 hours
  • Skill Level Beginner Level
  • Languages English
  • Includes Lifetime access
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    Available on iOS and Android
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About This Course

Published 12/2015 English

Course Description

Course Description

This SPSS data analysis course was created for one reason, which is to help anyone without statistics or mathematics background to analyze data in SPSS, choose the right descriptive statistics technique and write up the result of the findings with confidence.

The course covers everything from entering data into SPSS to interpreting the result and offers easy step-by-step guide to mastering descriptive statistics in SPSS.

Firstly, we will take you through the SPSS interface, how to work the system and avoid some of the mistakes people make when choosing variable types and format in SPSS. After that, we will dive into entering data into SPSS, sorting, editing and removing data, and most importantly how to transform any variable into a new variable with recode functions. We will then focus on descriptive statistics in SPSS and you will learn how to run the major descriptive statistics like Mean, Median, Mode, Standard Deviation and One-Samples t-test etc.

You will learn how to create graphs, plots and charts in SPSS and how to manipulate them to suit your needs.

Finally, we teach you the most important skill that most students wish they had; How to choose the appropriate statistical technique to analyze data in SPSS. We have broken down choosing the right test in SPSS into 3 simple steps:

  1. What is your research question?
  2. What is the type of variable and how many do you have?
  3. What is the level of measurement of your variables?

Using the three steps above, you will be able to choose the right test to use to analyze your data and we also use the flow chart to choose the right test for 20 real-life research question examples.

Upon completing this course, you will know when to use the following inferential statistic techniques:

  • Pearson Correlation
  • Spearman Ranked Order Correlation
  • Kendall's Tau B Correlation
  • Independent Samples T-test
  • Paired Samples T-test
  • Point Bi-Serial Correlation
  • Mann Whitney U Test
  • Kruskal Wallis
  • Mcnemar's Test
  • Chi Square
  • Linear Regression
  • Mutiple Regression
  • Binary Logistic Regression
  • Repeated Measures ANOVA
  • Between Subject ANOVA
  • Mixed/Split-Plot ANOVA
  • and so much more.

Course Materials

We use a mix of video materials, slides, template documents, SPSS data and output files to make sure this course is delivered effectively.

Taking this course is perhaps going to be the best decision you will ever make if you are going to use SPSS. It is not just about the content and context, it is more to do with the way the course is delivered and our ability to debunk complicated techniques. Our philosophy is; if you can't explain it simply, you don't understand it well enough. We explain everything using simple English to make sure you make the most of this course. This course should only take few days, but what you will learn will help you for the rest of your life.

What are the requirements?

  • Access to SPSS software is recommended

What am I going to get from this course?

  • Master the operation of SPSS and use it confidently
  • Enter and Code Data Correctly Into SPSS
  • Use Measures of Central Tendency and Dispersion in SPSS
  • Create and Edit Graphs, Charts and Plots in SPSS
  • Learn The Different Types of Inferential Statistics in SPSS
  • Understand the assumption of normality and no outlier and the graphical and statistical method to check them in SPSS
  • Analyse Your Data and Write-up The Results in APA and Harvard Style For Pearson, Spearman, Kendall's Tau B and Point-Biserial Correlation
  • Choose The Right Statistical Technique To Analyse Data in SPSS

Who is the target audience?

  • Ph.D, Masters and Undergraduate Students in Universities using SPSS for A Thesis, Dissertation or Statistics Module
  • Investors and Professionals with keen interests in sharpening their data analysis and statistic skills
  • Anyone Seeking to boost their statistics skill, while gaining an in-depth knowledge of Data Analysis in SPSS

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.


Section 1: Introduction To SPSS
Course Introduction

Downloading SPSS is quite straightforward. However, it can get a little confusing when you are installing the program. Upon completing this lecture, you will be able to download and install SPSS on a MAC or Windows OS. I also show you where you can get an affordable version of SPSS if your trial version has expired.

Section 2: Creating, Importing and Exporting Data in SPSS
Designing A Good Questionnaire and Codebook For SPSS

This lecture is about exploring SPSS and getting familiar with the software environment. You will be able to easily navigate the data view, chart editor, syntax and output screen once you complete this lecture.


This lecture shows you how to change the default option in SPSS. From changing the font size to changing the look of your table to the APA or Harvard style, you will be able to customize SPSS to suit your preferences.


If you intend to import your data or questionnaire responses from excel files and .txt file, this lecture shows you exactly how to go about doing so. After this lecture you will be able to import different file formats into SPSS and save it.

A practice Excel file and .txt file has been included. This will help you practice what you have learnt in this lecture.


As you begin to master how SPSS works, it becomes important to learn some shortcuts that can save your time. This lecture is all about shortcuts. After this course, you will know some of the most useful shortcuts in SPSS.

This lecture includes a keyboard shortcut file for Mac and Windows users.

Section 3: Creating, Managing and Manipulating SPSS Variables

At the end of this lecture, you will know the types of variables in SPSS and the advantage of using one over the other.


In this lecture, you will know all the levels of measurement in SPSS i.e nominal, ordinal, interval and ratio. This lectures will also demonstrate how the four levels of measurements differ and help you to develop the required skills to choose the most suitable level of measurements for your study.

There is a quiz at the end of this lecture to help you to grasp the level of measurements and code your data into SPSS correctly.


When you finish this lecture, you will be able to create your own variables in SPSS and use SPSS define variable functions to apply the same values to multiple variables. Dealing with multiple response questions is quite tricky and we have also shown you how to do that in this lecture.

After going through this lecture, you will also be able to sort and delete variables in SPSS.


You will be able to identify and specify missing values upon completing this lecture. You will be armed with the knowledge required to detect missing values and ensure that they are correctly accounted for before running any analysis in SPSS.


The compute variable function is one of the most important aspects of SPSS that gives you the flexibility to manipulate and carry out some serious scientific calculation with your data. At the end of this lecture, you will be familiar with computing variables and also be able to select cases of participants of interest in SPSS.


There are three main types of recoding in SPSS:

  1. Recoding String variables to numeric
  2. Recording existing variables to a new variable with a totally different values
  3. Recoding existing variables to a new variable in order to fix negative wordings.

At the end of this lecture, you will know all three recoding and be able to recode any data in SPSS.

Section 4: Descriptive Statistics: Measures of Central Tendency and Dispersion

In this introduction to descriptive statistics in SPSS, you will learn the importance of descriptive statistics. By the time you finish this lecture, you will have grasped the importance of descriptive statistics and be able to create frequency distribution in SPSS.


This lecture will walk you through measures of central tendency and by the end of the lecture you will be able to calculate mean, median, mode and sum in SPSS, as well as interpret the output professional.


This lecture will show you how to run standard deviation, variance, minimum, maximum and range in SPSS. Upon completing this lecture you will have mastered the measures of dispersion and you will be able to interpret the result.


After this lecture, you will understand the differences between percentiles and interquartile range, and learn how to calculate both in SPSS.


In this lecture, you will have a detailed explanation of z-scores, why it is important and when you need to calculate it. Upon completing this lecture, you will be able to calculate z-score and confirm whether it has been done accurately.


In this lecture you will learn how to:

  • Compare means for two or more groups.
  • Organize outputs be group and split files in SPSS.
Section 5: Creating and Interpreting The Outputs of Charts, Plots and Graphs

In this lecture, you will learn the two ways to create a histogram in SPSS and interpret the histogram.


After completing this lecture on creating bar graphs in SPSS, you will know the two ways to create:

  1. Simple Bar Graph
  2. Cluster Bar Graph
  3. Stacked Bar Graph

The rationale for choosing one over the other has also being provided in this lecture so you can choose the right one for the right purpose.


There are three main functions for creating a pie chart using SPSS dialog function, we show you each one of them and their limitations. After this lecture, you will be confident in your ability to create and manipulate a pie chart in SPSS.

Simple and Cluster Line Graphs
Creating Scatterplots in SPSS
Using Boxplots In SPSS
Editing Graphs and Charts In SPSS
Section 6: Descriptive Statistics: Preliminary Tests

This lecture will provide you with a background of normal distribution and briefly explain the two techniques of checking for normal distribution:

  • Graphical Techniques
  • Statistical Techniques

Using a histogram with a normal curve is the most common technique used for checking the assumption of normality. After this lecture, you will be able to check if your data is normally distribute. You will learn how to check a single variable for normality and also check grouped variables for normality.

We will checking for normality using:

  • Histogram
  • Normal Q-Q plots

After this lecture, you will be able to check if your variables are normally distributed and you will also be able to check if a variable is distributed for two or more categorical variables, which is important when comparing groups.

Statistical Method For Checking For Normality: Skewness and Kurtosis

In this lecture, you will learn how to check if your variable is normally distributed, using:

  1. Shapiro-Wilks
  2. Kolmogorov-Smirnov

You will also learn how Shapiro-Wilks test differs from Kolmogorov-Smirnov and when to use which one.

Transforming a Non-normal variable to normal in SPSS

Outliers can affect the accuracy of a statistical analysis in SPSS. In this lecture, you will learn the importance of checking for outlier and how to check outliers using SPSS. You also learn how to identify outlier cases and use common strategies to fix outliers. Most importantly, you will learn how to detect univariate outliers in SPSS using:

  • Graphical Method: Boxplots.
  • Statistical Method: Outlier Labelling rule.
  • Statistical Method: Using Z Scores.
Detecting Multivariate Outliers in SPSS
Section 7: Introduction To Inferential Statistics

In this lecture, you will understand the differences between independent and dependent variables. Several examples of independent variables and dependent variables have been included in this lecture to help you grasp the often confusing differences between the two variables.


In this lecture, you will understand the world famous significant or p-value. You will also understand why < .05 is an indication that a result is statistically significant.


Upon completing this lecture, you will be able to:

  1. Define a hypothesis.
  2. Determine when to use a hypothesis.
  3. Write a hypothesis.
  4. Differentiate between a null hypothesis and an alternative hypothesis.
  5. Understand the differences between type 1 and type 2 errors in hypothesis testing.

In this lecture, you will be able to:

  1. Identify parameter estimate inferential statistics
  2. Identify hypothesis testing inferential statistics
  3. Differentiate between parameter estimate and hypothesis testing inferential statistics.
Section 8: Correlation in SPSS
Introduction To Correlation in SPSS

In this lecture, I demonstrate how to run pearson correlation in SPSS and also check the main assumptions of pearson:

  • Linearity
  • Normality
  • No Outliers
  • Homoscedasticity

Finally, the result of the analysis was interpreted and I provide you with the APA and Harvard write up template so you can interpret your results and write it up easily. After completing this lecture, you will be able to use Pearson Correlation to analyze your data, check the assumptions and write up the result of your analysis.

Spearman Ranked Order Correlation
Kendall's Tau B Correlation
Point Biserial Correlation
Section 9: Choosing The Right Test

At the end of this lecture, you will be able to choose the right inferential statistics to analyze your data in SPSS. There is also an infographic at the end of this lecture to guide you through the process of choosing the right test to use in SPSS.

Choosing The Right Test in SPSS: Step 2
Choosing The Right Test in SPSS: Step 3
Choosing The Right Test in SPSS: Example Question 1 - 7
Choosing The Right Test in SPSS: Example Question 8 - 13
Choosing The Right Test in SPSS: Example Question 13 - 20

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Instructor Biography

SPSS Statisticians MyProjects, SPSS Specialist | Academic Tutors

We are specialists in SPSS Statistics, Data Analysis, and Academic Research Projects. For over 5 years, we have helped Undergraduate, Masters and P.h.D Students to successfully master the art and science of data analysis in SPSS. At MyProjects, our aim is to help students to realize their full potential by providing them with the best SPSS and academic courses, delivered in a professional and easy to understand manner.

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