Course Overview
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Expert| English[Auto-generated] What is SPSS Training?
SPSS is a widely used windows based program which is used for statistical analysis which helps to perform data entry and analysis to create tables and graphs. It is a comprehensive and flexible data management and statistical analysis solution. SPSS training is a statistical package which is used for beginning, intermediate and advanced data analysis. SPSS is mostly used by researchers, companies, government, data miners, and others. SPSS training is most often used in the field of social science. If one is very familiar with this program it will help them a lot in their future. SPSS is frequently updated.
Features of SPSS Training
- Easy to learn and use
- Different types of data management system and editing tools
- In-depth statistical capabilities
- Excellent reporting and presentation features
Benefits of SPSS Training Courses
Using SPSS software offers a lot of advantages which are listed below
- Effective data management
- Wide variety of options
- Better output to the users
- User friendly
- Easy access to basic functions like descriptive statistics
- Easy to find statistical tests
- Even the complex graphs can be created easily using SPSS Training
SPSS Courses objectives
At the end of this course you will be able to
- Know what is SPSS and how to use it
- Get an overview of the statistical software – SPSS
- Learn to enter different data in SPSS Courses
- Understand about the data management in SPSS
- Learn how to open an excel file in SPSS
- Know about data cleaning and filtering
- Learn how to analyze data in SPSS Courses using different statistical techniques
- Run statistical analysis on different type of data in SPSS
Pre Requisites for taking this SPSS Courses
This SPSS courses does not require much knowledge. A basic knowledge about computer and statistics and its related terminologies is enough to take up this course.
Target Audience for this SPSS Courses
Professionals, researchers and statisticians can take up this SPSS courses and it will be more useful for them. Other than that students and anyone who is interested in learning about SPSS can take up this course.
SPSS Courses Description
Section 1: Introduction
Introduction to SPSS
In this chapter, you will learn what is SPSS, its definition, its history. The section also lets you learn how to open SPSS in two ways. The other topics included in this section are
- A layout of SPSS – Data View and Variable view, SPSS Viewer window, Syntax window
- SPSS Menus and Icons – File, Edit, View, Data, Transform, Analyze, Graphs, Utilities, Add-Ons, Window, and Help.
- How to exit SPSS
Data entry of a Questionnaire format
In this section, you will learn how to enter questionnaire data into SPSS. It includes an example showing how to create a number of different variables. It also shows you the step by step procedure of creating the data file in SPSS, adding values for questions and how to perform appropriate analysis in SPSS
Data entry of MCQ question
The multiple response commands lets you analyze a number of separate variables all at the one time. This chapter explains to you how to input the data, set up variables for multiple response questions and analyze multiple choice questions.
Arranging columns in Ascending, Descending order
Sorting the data will help to rearrange the data in a specific order with respect to a specific variable. There are two ways of sorting the data – row sorting and column sorting. The different types of sorting are explained in detail in this chapter. The topics included are
- Sorting using the data view
- Sorting using the sort cases procedure
- Sort variables
- Choosing sort order under sorting types
Input Likert Scale
Likert Scale is most commonly used in research where questionnaire method is used. In this method, the responses are done using scales. The respondents specify their level of agreement or disagreement for a series of statements. In this chapter, you will learn how to summarize Likert scale the data in SPSS and how to do the analysis of the Likert scale data in SPSS.
Analyse mean, median, mode
This tutorial will show you how to use SPSS to perform descriptive statistics. The frequency command is used to calculate the mean, median and mode in SPSS. You can go to this command using Analyze à Descriptive à Frequencies. The step by step procedure is given in this chapter along with screenshots to make you easily understand the calculation of mean, median and mode in SPSS.
Section 2: Basic Data Management
Basic data operation
This section includes the following topics under it
- SPSS data preparation – This section includes details on inspecting the data for some common problems
- Initial data check – In this section you will learn how to do a quick case count and variable count.
- Inspect variable type – This tutorial shows you how to correct the errors in variables which should have been numeric
- Specify missing values – In this section, you will learn how to find the missing values quickly
- Inspect variables – Here you will learn if there are any unusual distributions of variables
- Inspect cases – Under this section, you will learn to exclude any bad cases from the data.
Data deleting & filtering
SPSS allows a part of the data to be selected for further analyses where the other unselected data remains unchanged. This section helps you to learn how to delete or filter certain cases from an analysis in SPSS.
To delete cases the SELECT IF option is used
Data in SPSS can be sorted and filtered using different ways. Data can be sorted in the Data editor window by right-clicking and selecting the Sort Ascending or Sort Descending option. Now the variables will be sorted. The Select Cases function can also be used to select specific cases in SPSS and filter them. Filtering can be done according to one condition and according to multiple conditions. These filtering options are explained in detail with example and screenshots.
Opening an excel file in SPSS
In this section, you will learn how to import an excel file into SPSS training using step by step guide along with screenshots to make you easily understand.
Performing independent samples t-test
Independent samples t-test compares the means of two independent groups to find out if the means are significantly different. The variable used here is dependent variable and independent variable. There are six basic assumptions of independent samples t-test. In this section, we will see the SPSS statistical procedure of performing an independent samples t-test. An example is given along with step by step process of calculation.
Performing paired t-test
Paired t-test compares two means of the same units which are tested at the different point in time or in two different situations. The variable used in this test are dependent or test variable. There are four basic assumptions of the paired t-test. In this section, we will see the procedure of performing a dependent or paired t-test in SPSS using an example.
Section 3: Correlation Analysis and Tests
Correlation Analysis
This analysis is used to test if the two metric variables are linearly related in some population. The topics included in this section are
- Example of Correlation analysis
- Quick data check
- Assumptions of correlation test
- Running SPSS Correlation test in SPSS
- SPSS correlation test output
- How to report a correlation test output in SPSS
Wilcoxon test
The Wilcoxon Sign test is used to compare the averages of two dependent samples. The Wilcoxon test can be found in Analyze à Non Parametric tests à Legacy dialogs à 2 related samples. The Wilcoxon Signed-rank test has three basic assumptions. These assumptions are explained in this chapter. The section also provides a step by step procedure to perform Wilcoxon Signed Rank test in SPSS using an example and the required screenshots.
Mann-Whitney Test
The Mann-Whitney U test is used to compare the mean. It compares the differences between the two independent groups when the dependent variable is either ordinal or continuous. There are four basic assumptions of this test and these assumptions are explained in detail under this chapter.
To go to this test you should go to Analyze à Non-parametric tests à Legacy Dialogs à 2 Independent samples. After this, you will be presented with a step by step procedure to calculate the Mann-Whitney U test using SPSS.
Chi-Square Test
Chi-Square test is used to find out if there is any relationship between two categorical variables. This section explains the two assumptions of Chi-Square test. An example is given to explain the chi-square test using step by step guide in SPSS. To use chi-square test, on the menu bar go to Analyze à Descriptive Statistics à Crosstabs.
One-way ANOVA
One way ANOVA is used to find out if there is any significant difference between the means of two or more independent groups. There are six assumptions of one way ANOVA and these are explained in brief in this section. The other topics included in this section are
- One Way ANOVA example in SPSS
- Quick Data check
- Running One way ANOVA in SPSS
- One way ANOVA output in SPSS
- Reporting a one way ANOVA in SPSS
Error Bar Chart
Error bar chart is used to plot a group of variables. This section gives you step by step procedure of creating an error bar chart in SPSS with a neat example.
One-way Within Subjects ANOVA
This type of ANOVA is used to compare the means of two or more groups where the variables of all the groups are same but tested under different situation or condition. It has five assumptions and all these assumptions are explained in detail in this section. An example is given and the steps to perform Repeated measures ANOVA in SPSS are given with screenshots for easy understanding.
Single-Linear & Multi-Linear Regression
Linear regression is used to find out the value of one variable based on the value of another variable. This section has the following topics under it
- What is a simple linear regression
- Assumptions
- Example and steps to perform simple linear regression
- What is multiple linear regression
- Assumptions
- Example and steps to perform multiple linear regression
Dummy Variable
This section explains what is a dummy variable in SPSS, why it is used, how it is created, dummy variable syntax example and labeling the dummy variable
Summary of SPSS
This section again gives you an overview of SPSS and all the basic concepts of SPSS. It explains the benefits and uses of SPSS in various fields.
SPSS Training FAQ’s General Questions
- How to contact in case of any queries?
If you have any queries you can post them in the discussion section or you can contact the customer support center which is available 24*7 for your support.
- After taking up a course can I take a break and continue the course later?
You will be given a specified period for taking the course. And within that particular period you can take breaks and continue with the course later but you need to complete the course within that period.
SPSS Training Testimonials
Stephaine
This course covers almost all of the fundamentals of statistics and how to run analysis in SPSS. The examples are more simple and neatly explained making the learning process easy for us. This course helped me to complete my project using SPSS in a short period of time. I would definitely recommend this course.
Marsha
Whether you are new to SPSS or already an user of SPSS, this course works great. It is a good course to review all the basics of SPSS. It was of great value for the cost of the course. The content flow was good and the explanations were great and complete. The quality of the course is excellent. Thanks to educba for this course and I look forward to more courses on advanced statistics.
| Where do our learners come from? |
| Professionals from around the world have benefited from eduCBA’s SPSS Training Courses – Analyze Data for Statistical Analysis Courses. Some of the top places that our learners come from include New York, Dubai, San Francisco, Bay Area, New Jersey, Houston, Seattle, Toronto, London, Berlin, UAE, Chicago, UK, Hong Kong, Singapore, Australia, New Zealand, India, Bangalore, New Delhi, Mumbai, Pune, Kolkata, Hyderabad and Gurgaon among many. |
