| COURSE : DATA ANALYTICS FOR LEAN SIX SIGMA | |
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| Course Overview | This training helps you to analyse the data. It is also extensively used by Six Sigma Experts a is an important part of studying data, particularly in the Measure and Analyse phases of DMAIC. This training provides a quick, effective solution for the level of analysis. |
| Training Duration | Total Training Hours : 28-30 Hours Training Duration : 1 Week Total Training Days : 4-5 Working Days |
| Training Schedules | Weekdays (Sunday to Thursday)Regular Sessions : 4 Hrs Per day WeekEnds (Friday & Saturday)Fast Track Sessions: 6-8 Hours per day |
| Certifications: | Weekdays (Sunday to Thursday)Regular Sessions : 4 Hrs Per day WeekEnds (Friday & Saturday)Fast Track Sessions: 6-8 Hours per day |
| Tests | Yes |
| Learning Aids | Yes |
| Course Material | Hard & Soft Copies of Study Material |
| Language of Instruction | English |
| Instructor Helpline | Yes 1. Email 2. Social Media (For Emergency requirements) |
| Registration Requirements | 1. Passport Copy 2. Curriculum Vitae 3. Passport size photographs 4. Course Fee |
| Mode of Payment: | Cash / Cheque / Credit Card / Bank Transfer. |
| Eligibility Criteria (Who should attend this training) |
Managers, professionals, team leads and employees who are expected to lead improvement efforts in their work areas, or those who aspire to be in such roles, should attend this programme. You should be a Graduate with a good Bachelor’s degree or a Polytechnic Graduate with at least 1 year of working experience. You should also be someone who would be comfortable working in and leading project teams. Organisation leaders who would like to learn what it would take to manage projects in their organization are also welcome. |
| Course Benefits |
Measure Phase |
| Course Contents / Outline |
ypes of Data Data Collection & Display Frequency Table Concentration Diagrams Stem and Leaf Diagrams Frequency Distribution Histogram Descriptive Statistics Definitions Population and Sample Why do we need samples? Different methods of sampling Estimating Sample Size Properties of data Central Tendency Mean, Median, Mode & Quartiles Dispersion Range, Variance, Standard Deviation & IQR
Understanding Behaviour of collected data Trends & Patterns in Data Trend Analysis Variation & its consequences Stability Analysis Test for Normality Process Capability Cp & Cpk DPMO Standard Normal Distribution (Z) Basic Data Analysis Tools Histogram Pareto Analysis Box Plot Analyse Testing of Hypothesis t – Test ANOVA Regression Analysis Regression and Correlation Determination Coefficient Simple Linear Regression Curvilinear Regression Overview to Design of Experiments Control Phase Control-Charts Individual Values Variables Attributes
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