Determining Sample Size And Power in Research Studies

Unlock the Power of Statistical Analysis to Uncover Relationships and Make Informed Decisions

Learn R, data analysis, visualization, inference, and regression through real-world statistical practice.

Statistics is a thought process. In this comprehensive introduction to statistical methods and data analysis, the process is presented utilizing a four-step approach: 1) gathering data, 2) summarizing data, 3) analyzing data, and 4) communicating the results of data analyses

PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough. PASS lets you solve for power, sample size, effect size, and alpha level. It automatically displays charts and graphs along with numeric tables and text summaries in a portable format that is cut and paste compatible with all word processors so you can easily include the results in your proposal. PASS is a standalone system. Although it is integrated with NCSS, you do not have to own NCSS to run it. You can use it with any statistical software you want. PASS 2008 runs under Windows Vista, XP, 2000, NT, ME, 98, and 95.

Practical solutions to Machine Learning problems, avoiding roadblocks while working with Python data science ecosystem.