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Statistician in Scientific Research Course
Discover the potential of data through our Course on Statistical Analysis for Scientific Research. Delve into key areas such as Regression Analysis, learning to understand results and differentiate between correlation and cause-and-effect. Investigate Side Effects Analysis using demographic and group-based data insights. Improve your abilities in Descriptive Statistics, Hypothesis Testing, and Data Exploration Methods, including data preparation and visual representation. Finish with practical suggestions for upcoming studies. Enhance your statistical capabilities now!
- Become proficient in regression analysis: Understand the results and tell the difference between correlation and cause.
- Perform side effects analysis: Study population data and identify data trends.
- Use descriptive statistics effectively: Apply measures of average and variation appropriately.
- Carry out hypothesis testing: Develop hypotheses and understand the meaning of different test results.
- Explore data techniques: Prepare data, handle it before analysis, and deal with missing data effectively.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Discover the potential of data through our Course on Statistical Analysis for Scientific Research. Delve into key areas such as Regression Analysis, learning to understand results and differentiate between correlation and cause-and-effect. Investigate Side Effects Analysis using demographic and group-based data insights. Improve your abilities in Descriptive Statistics, Hypothesis Testing, and Data Exploration Methods, including data preparation and visual representation. Finish with practical suggestions for upcoming studies. Enhance your statistical capabilities now!
Elevify advantages
Develop skills
- Become proficient in regression analysis: Understand the results and tell the difference between correlation and cause.
- Perform side effects analysis: Study population data and identify data trends.
- Use descriptive statistics effectively: Apply measures of average and variation appropriately.
- Carry out hypothesis testing: Develop hypotheses and understand the meaning of different test results.
- Explore data techniques: Prepare data, handle it before analysis, and deal with missing data effectively.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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