Award in Statistical Analysis: Introduction to R

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Course Summary

Course code

DS-SC-001

MQF Level

Credits

Duration

8 weeks - 1 session per week

Awarding Body

IPD - Institute of Professional Development

Start Date

TBA

Price

€495

Delivery Method

Face to face - Classroom based

Course Description

This course provides the basic necessary knowledge for participants to understand the language of statistics. This course provides a good platform for anyone that would like to understand basic statistical reports or to pursue further to other statistical topics. Furthermore, participants will learn how to use the software R and how to implement such analysis in R.

By the end of the programme learners will be able to

Interpret effectively basis statistics
Write appropriate coding in R
Apply R effectively
Conduct basic statistical analysis
Statistical inference
Generalisation of results using statistical tests
Regression models and hence using such models to apply predictions

Modules

By the end of this module, participants will be able to:

Apply programming in R
Reading data into R
Accessing R packages
Writing R functions
Familiarizing with R code
Understand and apply basic statistical analysis including visualising of data, frequency tables and descriptive statistics.
Understand Sampling theory and methodology
Understand Sampling techniques including Systematic Sampling, Stratified Sampling, Random Sampling, Cluster Sampling and Multistage sampling
Understand and calculated sample sizes
Understand and apply Confidence intervals
Understand and apply Hypothesis testing involving one sample, two samples
Understand and apply several means tests and tests for associations. Such tests shall include: Independent samples t-test, ANOVA test, Chi-Squared test, Correlation test and Paired samples t-test
Understand and apply regression analysis including both simple linear and multiple linear regression

Target Audience

The target audience for this Award is:

individuals working in organisations who wish to gain knowledge about statistical analysis and its application to work
individuals who are following a course in higher education and wish to brush up their statistics knowledge

Entry Requirements

A qualification at O'level standard or MQF Level 3 in mathematics or equivalent

Additonal Information

Hours of total learning

This course has 100 total hours of learning split as follows:

Total contact hours: 25
Practice hours: 10
Self Study hours: 50
Assessment hours: 15

Attendance

Short course – part-time

Course dates
October – 12th, 20th & 27th
November – 3rd, 10th, 17th & 24th
December – 1st

Course time
4:15pm to 7:30pm

Course Venue
Delivered at IPD premises

Teaching and assessment

A mixture of presentations and practice sessions using different computer software will be used during this course. Dummy data for analysis will be provided by the Institute.

The course is assessed through an assignment to be submitted within 4 weeks from the end of the course.

The assignment shall include a dataset that participants need to analyse. Furthermore, participants will be presented with 4 specific questions they need to answer. Throughout this assignment, participants will be assessed on their proficiency in statistical analysis through the use of the ‘R’ software.

You are required to use your laptop for this course.

For further information about this course kindly contact the Institute.

Tutors

Dr. Vincent Marmara

Apply Now

To apply for any of our courses please complete the admissions form above by clicking on the “Apply Now” button. Make sure you check the entry requirements for the course you are applying for. If you have any queries about the course you are interested in, please contact us at [email protected]. We actively encourage applications from individuals with non-traditional and/or non-standard qualifications and experience. We are firm believers in diversity because we believe that this enhances the quality learning experience, we aim to provide at IPD. Our admission decisions are therefore based on your academic credentials as well as on other work and life experiences you may have.