Introduction to Statistics (Hot)

Course Code: STA1001

Duration: 2 days

Time: 9 am – 5 pm

Introduction to Statistics Description

This two-day introductory statistics course is the most practical and comprehensive introduction to the many facets of statistics concepts and applications you’ll find anywhere.

As a participant, you will get a thorough briefing in the nuts and bolts of Statistics.

This qualification is primarily aimed towards:

• Those who require a basic understanding of the statistics;
• Those who need understanding of how statistics can be used to enhance the quality of commercial data analysis report and academic research paper;
• Data analysis professionals or others working within an organization that has adopted and adapted statistics who need to be informed about, or contribute to an ongoing service improvement.

Course Outline

Module 1 – Introduction to Statistics

• Objective and Scope of Statistics
• Study Design, Types of Studies, Variables
• Bias, Sample Size Issues
• Data Classification

Module 2 – Graphing Data

• Bar charts & pie charts
• Histograms & stem-and-leaf plots
• Box plots
• Scatter plots

Module 3 – Numerical Summaries

• Summarising Numerical Data
  • Measures of centre and spread
• Summarising Categorical data
  • Proportions and Percentages
• Population distributions

Module 4 – The Normal Distribution

• Introduction to probabilities
• Normal distribution
• The standard normal distribution
• z-scores
• More on probabilities

Module 5 – Confidence Interval

• Confidence interval for population mean
• Confidence interval for population proportion
• Introduction to the t-distribution

Module 6 – One Sample Hypothesis Tests for a population mean

• z-test for a population mean
• t-test for a population mean

Module 7 – Comparing Means

• Independent data
• Paired data

Module 8 – Hypothesis Test for Population Propotions

• One-sample z-test for a population proportion
• Inferences about two population proportions
• Revision – hypothesis testing

Module 9 – Simple Linear Regression Part 1

• Dependent and independent variables
• The Least Squares Regression Line
• Assumptions of the linear model
• Testing the slope of the line

Module 10 – Simple Linear RegressionPart 2

• Making predictions
• Goodness-of-fit statistic
• Correlation coefficient

Who will benefit most ?

• The statistics qualification is open to any individuals who may have an interest in the subject and enable the holders of the qualification to apply the statics practices for data analysis without further guidance.