To [course_title] is designed to provide you with basic knowledge and skills to independently design, execute and explain the results of data analysis in the context
of a genomics/proteomics experiment. Through this course you will learn advanced techniques to analyze genomic data, how to structure, annotate, normalize, and interpret genome-scale assays, how to bridge diverse genomic assay and annotation structures to data analysis and research presentations via innovative approaches to computing, how to analyze data from several experimental protocols, using open source software, including R and Bioconductor.
Assessment
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
Certification
Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.
Having an Official Edukite Certification is a great way to celebrate and share your success. You can:
- Add the certificate to your CV or resume and brighten up your career
- Show it to prove your success
Course Credit: Harvard University.
Course Curriculum
Introduction | |||
Introduction to statistics and R for the Life Sciences | 00:02:00 | ||
Lesson 1 | |||
Getting Started with | 00:06:00 | ||
GitHub | 00:02:00 | ||
RStudio | 00:01:00 | ||
Using the Textbook | 00:02:00 | ||
RStudio for Organization | 00:06:00 | ||
Introduction to dplyr | 00:09:00 | ||
Lesson 2 | |||
Motivation | 00:05:00 | ||
Introduction to Random Variables | 00:04:00 | ||
Probability Distributions | 00:03:00 | ||
The Normal Distribution | 00:07:00 | ||
Populations, parameters, and sample estimates | 00:05:00 | ||
Central Limit Theorem (CLT) | 00:07:00 | ||
CLT in Practice | 00:04:00 | ||
T-test | 00:06:00 | ||
T-test in practice | 00:03:00 | ||
Lesson 3 | |||
Introduction to Inference | 00:02:00 | ||
Confidence Intervals | 00:08:00 | ||
Power Calculations | 00:07:00 | ||
Monte Carlo Simulation | 00:06:00 | ||
Association Tests | 00:02:00 | ||
Lesson 4 | |||
Histogram | 00:04:00 | ||
qq-plot | 00:02:00 | ||
Boxplot | 00:02:00 | ||
Scatterplot | 00:07:00 | ||
Symmetry of Log Ratios | 00:02:00 | ||
Plots to Avoid | 00:05:00 | ||
Avoid Pseudo 3D | 00:02:00 | ||
Median, MAD, and Spearman Correlation | 00:02:00 | ||
Mann-Whitney-Wilcoxon Test | 00:03:00 | ||
Assessment | |||
Submit Your Assignment | 00:00:00 | ||
Certification | 00:00:00 |
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