ABOUT THIS COURSE
Imagine a situation where you not only produce data analysis reports, but also use the R programming language to visualize the data and derive statistical conclusions like a boss. Statistics with R is the best of both worlds, equipping you with the specialization of both a strategist and a data scientist.
Learn the most in-demand technology and business-oriented skill and find a prosperous way to make a great career in the field of data and analytics.
Rated Top 3 in Analytics programs in the country, Praxis Business Schools has designed the program through its Industry veterans in the Analytics domain.
- Learn to use R to model statistical relationships using graphs, calculations, tests, and other analysis tools. Learn how to enter and modify data; create charts; examine outliers; calculate correlations; and compute regressions, bivariate associations, and statistics for three or more variables.
KEY TOPICS COVERED
- Introduction to data; data basics; overview of data collection principles
- Experiments - principles of experiment design
- Introduction to probability, Bayes’ rule
- Distributions - discrete distributions; continuous distributions
- Introduction to linear regression
- Correlation - line fitting - fitted values - residuals
- Basic introduction to multiple regression
- Foundations for inference and estimation· variability in estimates, sampling distribution, confidence intervals
- The margin of error and ascertaining a sample size
- Foundations for inference and hypothesis testing
- Nearly normal population with known sd
- Hypothesis testing framework, two-tailed and one-tailed tests
- Testing hypothesis using confidence intervals and critical z values
- One-sample means with the t distribution with unknown population sd
- Inference for a single proportion, decision errors (type 1 and 2)
- Hypothesis testing using p-values, choosing a significance level
- Power and the type 2 error rate, linear regression and multiple regression
- Introduction to f-statistic, hypothesis tests, intervals
- A coefficient of multiple determination
- Interpreting the model output.
PRE-REQUISITES TO REGISTER FOR THE COURSE:
- R programming and Statistics