SPSS: Learn SPSS

SPSS Statistics is a statistics and data analysis program for businesses, governments, research institutes, and academic organizations. In this course, Barton Poulson takes a practical, visual, and non-mathematical approach to SPSS Statistics, explaining how to use the popular program to analyze data in ways that are difficult or impossible in spreadsheets, but which don't require you to master programming languages like Python or R. From importing spreadsheets to making data visualizations to calculating descriptive statistics, Barton covers all the basics, with an emphasis on clarity, interpretation, communicability, and application. This course is ideal for first-time researchers and those who want to make the most of data in their professional and academic work.

• Making data visualizations
• Creating regression variable plots
• Importing data and recoding variables
• Computing frequencies and correlations
• Reliability analysis
• k-means clustering
• Decision tree classification
• Analyzing data
• Building predictive models
• Exporting your work

Explore how to run tests for academic research with SPSS, the leading statistical software. In this course, Yash Patel dives into SPSS, focusing on how to run and interpret data for the most common types of quantitative tests. Topics include t-tests, analysis of variance (ANOVA), and understanding the statistical measurements behind academic research. Review the tenants of qualitative testing, including the central theorem, P values, and confidence intervals, and specific use cases for tests in SPSS. For each type, Yash provides some general guidelines and assumptions, along with a challenge and solution exercise to practice what you've learned.

• Quantitative vs. qualitative analysis
• Sample size considerations
• Normal distribution
• Estimating the population mean
• One-sample t-test
• Paired-sample t-test
• One-way and two-way ANOVA
• Repeated measure ANOVA