The course provides you 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.
The Data Analysis Certification is an accreditation that endorses you both for the knowledge and practical application of best practices used in analyzing statistical data.
The certification is the result of a complex, experiential learning program that has 3 sections: pre-course activities, core-course exercises and post-course assignments.
You will acquire the tools and skills needed to develop complex data analysis, useful for the processing and interpretation of data and relevant for your company's profile.
Validate your expertise!
The Data Analysis Certification is an accreditation that endorses you both for the knowledge and practical application of best practices used in analyzing statistical data.
The certification is the result of a complex, experiential learning program that has 3 sections: pre-course activities, core-course exercises and post-course assignments.
You will acquire the tools and skills needed to develop complex data analysis, useful for the processing and interpretation of data and relevant for your company's profile.
Validate your expertise!
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.
- Access a free learning module on Performance Measurement Maturity Assessment.
Course Content
Module 1 - Business Understanding
Module 2 - Data Collection
Module 3 - Data Preparation
Module 4 - Data Exploration
Module 5 - Descriptive Statistics
Module 6 - Sampling
Module 7 - Estimation of Population
Module 8 - Hypothesis Testing
Module 9 - Z-Test and T-test
Module 10 - ANOVA Test
Module 11 - Chi-Square Tests
Module 12 - Regression Analysis
Module 13 - Multiple Regression
Module 14 - Time Series
Module 15 - Revision
Speakers
Ágnes IlyésSubject Matter Expert
Ágnes holds valuable experience in data analysis, as during both her university and working years she had participated in numerous marketing related research projects where survey based primary researches were conducted and a lot of data were evaluated.
She mainly uses SPSS statistical program to analyze data. She has experience with the following analyses: Chi2 analysis, Variance analysis, Correlation analysis, t-test, factor- and cluster analysis.
Ágnes also deepened her knowledge by teaching interferential statistics as an external lecturer on the university, on economics and business administration faculty, marketing specialization.
As a Business Research Analyst at the KPI Institute she also has numerous possibilities to capitalize her experience in this field.
Who Should Attend
Professionals interested in Data AnalysisThe 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.
Management Representatives
The course is addressed to Managers, HR Representatives, Analysts, Auditors or Logistics and Acquisitions Experts, as well as to professionals from other business areas, who deal with data analysis.
Data Analysis Experts
The course is ideal 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.)
