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Master SPSS: Descriptive Stats & Correlation
Rating: 5.0 out of 5(1 rating)
101 students

Master SPSS: Descriptive Stats & Correlation

Use SPSS for data analysis, descriptive statistics, charts, boxplots, and correlation step-by-step
Created byTraining Que
Last updated 4/2026
English

What you'll learn

  • Summarize and describe your dataset using descriptive statistics (mean, median, standard deviation, etc.)
  • Generate and customize visualizations in SPSS, including bar charts, histograms, and scatterplots
  • Understand and apply correlation analysis to explore relationships between two variables
  • Interpret SPSS output tables with confidence
  • Choose the right tools in SPSS to match your data type and analysis goal
  • Present your results clearly and effectively in reports or research papers

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Course content

4 sections • 12 lectures • 1h 1m total length

  • Types of Descriptive Statistics (Mean, Median, Mode, Std. Dev.)5:41
  • Running Frequencies & Descriptives3:55

    Learn to run frequencies and descriptives in SPSS to summarize categorical and numeric data, view distribution, and obtain statistics like mean and standard deviation for cleaning and reporting.

  • Explore Function for Summary Tables4:38

    Explore the SPSS Explore tool to generate descriptive statistics, tests of normality, outlier detection, and plots like boxplots and histograms for continuous data across groups.

  • Interpreting Output Tabless5:20

    Learn to read SPSS output tables in the output viewer from frequencies, descriptives, and explore analyses, including mean, standard deviation, and minimum and maximum, for clear data interpretation.

  • Mini-test 1

Requirements

  • Basic familiarity with SPSS interface (recommended but not required)
  • Access to IBM SPSS Statistics software (any recent version)
  • Basic understanding of research concepts such as variables and data types
  • No advanced statistical knowledge required

Description

“This course contains the use of artificial intelligence.”

In this course, you’ll learn how to use SPSS to perform descriptive statistics, create professional charts, and run correlation analysis with clarity and confidence.

This is Part B of the “Getting Started with SPSS” series and focuses on helping you summarize, visualize, and interpret your data effectively.

We begin with core descriptive statistics. You will learn how to calculate and interpret mean, median, mode, and standard deviation, and understand when to use each measure. You’ll practice generating summary tables using the Frequencies, Descriptives, and Explore functions in SPSS and learn how to interpret output tables correctly.

Next, we move into data visualization. You’ll create bar charts, histograms, pie charts, and boxplots. You’ll also learn how to customize titles, labels, and colors to make your charts clear, professional, and presentation-ready. By the end of this section, you’ll be able to explore data distributions and identify patterns or outliers visually.

In the final module, you’ll explore correlation analysis. You’ll understand the difference between Pearson and Spearman correlation, learn how to run a correlation matrix in SPSS, and interpret the coefficient table—focusing on strength, direction, and statistical significance.

This course is ideal for students writing a thesis or research paper, professionals analyzing survey data, and beginners who want a practical, step-by-step guide to descriptive statistics and correlation in SPSS.

By the end of this course, you’ll be able to confidently summarize datasets, visualize data effectively, and interpret relationships between variables using SPSS.

Who this course is for:

  • Students writing a thesis, dissertation, or class project that requires analyzing data
  • Researchers in social sciences, education, psychology, public health, and beyond
  • Professionals who need to analyze survey or experimental data
  • Beginners who’ve started working with SPSS and want to level up their skills in data summary and visualization
  • You — if you want a no-nonsense, step-by-step guide to SPSS that actually makes sense

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