Duration
5 days (4hr/day)
Course Description
The Data Analysis Professional is the first level of our Data Analysis Program. It is a hands-on training course aimed at equipping you with the necessary concepts and tools needed to perform basic statistical and analytical reporting activities, in order to generate value out of the existing data. The course provides you with the knowledge required for understanding distinct methods used in analyzing data, statistical interpretation of quantitative and qualitative data, and becoming proficient in using key Microsoft Excel features, by building frequency and conditional tables, creating different types of charts, finding correlations and relationships between variables, hypothesis testing and statistical modeling.
Target Audience
- The course is designed for anyone who has basic mathematical training and basic competences in using Microsoft Excel. Statistical knowledge, intermediate or advanced knowledge of Excel, practical experience with data analysis and related duties are not necessary but may contribute to a better understanding and more in-depth coverage of the course content. Diversity of participants’ background may help in a thorough coverage of the entire syllabus.
- The course is addressed to managers, Human Resources Representatives, analysts, auditors or logistics and acquisitions experts, as well as to professionals from other business areas, who deal with data and analysis on daily basis.
- The course may also be a starting point for those interested in pursuing career opportunities in data analysis, data modelling and related activities (e.g. campaign management, data mining, statistics, risk management, reporting, data processing for survey analysis etc.).
Benefits
- Obtaining the most relevant data, by setting up a customized data analysis process;
- Understanding the data analysis process, its methodology, and logical framework;
- Obtaining the necessary knowledge to analyze complex data and to interpret results;
- Improving the organization’s decision-making process, by gaining knowledge on data analysis and interpretation;
- Receiving the management team’s buy-in, by sharing with them the utility of implementing a customized data analysis methodology in daily business activities;
- Obtain 40 CPD credits to include in your CPD records for your professional body, institute, regulator or employer.
Learning objectives
- Developing a hands-on, practical overview of data analysis and connected topics;
- Integrating statistical concepts and analysis tools that are widely used in corporate analytics environments;
- Analyzing examples of practical applications for statistical methods, used in solving real-life business issues;
- Acquiring mastery of Microsoft Excel Data Analysis features, by learning to use statistical techniques through practical examples.
Day 1 Understanding Data Analysis
Course context
- Introduction of the participants;
- Expectations setting;
- Learning objectives formulation;
- Course agenda presentation.
Business Understanding
- Definition of Data Analysis
- Types of Data Analysis
- Data Analysis Process
- Data Analysis Governance
- Data Analysis in Business Capabilities.
Data Preparation
- Types of Data Sets
- Data Quality
- Data Cleaning
- Data Aggregating
Day 2 Understanding Data Analysis
Data Exploration
- Frequency Tables
- Qualitative Charts
- Quantitative Charts
- Structure Charts
Descriptive Statistics
- Univariate Analysis
- Bivariate Analysis
Sampling
- Population and Sample
- Sampling Techniques
- Sampling Determinations
Day 3 Core of Data Analysis
Estimation of Population
- Inferential Statistics Types
- Sources of Estimation Errors
- Central Limit Theorem
- Normal Distribution and T-Distribution
- Population Interval Estimation
Hypothesis Testing
- Hypothesis Testing Procedure
- Type I and Type II Errors
- Level of Significance and p-Value
- Different Types of Hypothesis Testing
Z-Test and T-Test
- One Sample Analysis
- Two Independent Samples Analysis
- Two Dependent Samples Analysis
Day 4 Advanced Data Analysis
Analysis of Variance
- F-Distribution
- ANOVA Test procedure
- Three or more Independent Samples Analysis
Chi-Square Tests
- Chi-Square Distribution
- Goodness of fit Test
- Test of Independence
Linear Regression Analysis
- Least Square Method
- Coefficient of Determination and Correlation
- Standardization; Homogeneity
Day 5 Advanced Data Analysis
Multiple Regression Analysis
- Multiple Coefficient of Determination
- Multicollinearity
- Variance Inflation Factor
Time Series
- Trend Component
- Cyclical Component
- Seasonal Component
- Irregular component
- Moving Average
Review and certification exam
- Course Review
- Certification Exam
Programme scope, delivery arrangements and suitability are confirmed during enquiry.