INTRODUCTION TO STATISTICS WITH R
- Professional Development course
The world of practical business analytics has moved to the R environment. The R environment has been created by the world’s most highly regarded statisticians, graphics experts and data analysts. It is open source, free and updated daily. There are many sources of continuous learning of R available for free.
This course provides a basic introduction to practical statistical concepts and techniques as they apply to the analysis and presentation of data in marketing research. This is a hands-on course, more of a workshop, where participants will learn how to use the R statistical environment and the Deducer GUI to access research data, clean that data, reshape it, and apply basic statistical methods to typical problems that arise in marketing. This course is developed for those who have very little, if any, statistical background and for those who want to move from a commercial statistical package to R.
MAJOR TOPICS COVERED IN THIS COURSE INCLUDE
- The research process – Research questions, research design & hypotheses
- Data – where does it come from & what should you I do with it?
- Statistical tools – R, RStudio, Deducer
- Data sets
- Basic data exploration – tables & graphs
- Descriptive statistics
- Measures of central tendency and variation, visualization of survey and research data, building analytical intelligence using Deducer
- Cross-tabs and the Chi square test,
- Confidence intervals
- Differences between two groups: Independent & paired t-tests, z-test
- Correlation, simple linear regression
- Multiple linear regression
- Logistic regression
Upon completion of this course, students will be able to complete the following key tasks:
- Use R (RStudio and Deducer) to access and configure marketing research data;
- Review and clean data sets before analyzing the data they contain;
- Decide on appropriate statistical techniques for analyzing data;
- Perform the most typically used statistical methods using R;
- Determine whether statistical estimates are significant or not;
- Define suitable models for data analysis (e.g. linear regression);
- Interpret statistical findings in effective ways for management and clients.
||Members seeking CMRP designation
||Everyone who has designed a survey
||Little or no exposure
||Less than 2 years experience
||2-8 years experience
||8+ years experience
- Course Length: 1 Day
- Check-in: 8:30 am
- Classes: 9 am - 5 pm
- Lunch will be provided
- For terms and conditions, click here
The venue address will be sent to you as part of your course registration confirmation.
*Plus applicable taxes
MRIA courses and their administration are subsidized by members' fees. Therefore, members enjoy a reduced cost for courses.