168 Statistics courses

Business Networking 1 Day Training in Southampton

Lean Six Sigma Black Belt Certification Program This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

Lean Six Sigma Black Belt Certification Program: In-House Training This course is specifically for people wanting to become Lean Six Sigma Black Belts, who are already Lean Six Sigma practitioners. If advanced statistical analysis is needed to identify root causes and optimal process improvements, (Lean) Six Sigma Green Belts typically ask Black Belts or Master Black Belts to conduct these analyses. This course will change that. Green Belts wanting to advance their statistical abilities will have a considerable amount of hands-on practice in techniques such as Statistical Process Control, MSA, Hypothesis Testing, Correlation and Regression, Design of Experiments, and many others. Participants will also work throughout the course on a real-world improvement project from their own business environment. This provides participants with hands-on learning and provides the organization with an immediate ROI once the project is completed. IIL instructors will provide free project coaching throughout the course. What you Will Learn At the end of this program, you will be able to: Use Minitab for advanced data analysis Develop appropriate sampling strategies Analyze differences between samples using Hypothesis Tests Apply Statistical Process Control to differentiate common cause and special cause variation Explain and apply various process capability metrics Conduct Measurement System Analysis and Gage R&R studies for both discrete and continuous data Conduct and analyze simple and multiple regression analysis Plan, execute, and analyze designed experiments Drive sustainable change efforts through leadership, change management, and stakeholder management Successfully incorporate advanced analysis techniques while moving projects through the DMAIC steps Explain the main concepts of Design for Six Sigma including QFD Introduction: DMAIC Review IIL Black Belt Certification Requirements Review Project Selection Review Define Review Measure Review Analyze Review Improve Review Control Introduction: Minitab Tool Introduction to Minitab Minitab basic statistics and graphs Special features Overview of Minitab menus Introduction: Sampling The Central Limit Theorem Confidence Interval of the mean Sample size for continuous data (mean) Confidence Interval for proportions Sample size for discrete data (proportions) Sampling strategies (review) Appendix: CI and sample size for confidence levels other than 95% Hypothesis Testing: Introduction Why use advanced stat tools? What are hypothesis tests? The seven steps of hypothesis tests P value errors and hypothesis tests Hypothesis Testing: Tests for Averages 1 factor ANOVA and ANOM Main Effect Plots, Interaction Plots, and Multi-Vari Charts 2 factor ANOVA and ANOM Hypothesis Testing: Tests for Standard Deviations Testing for equal variance Testing for normality Choosing the right hypothesis test Hypothesis Testing: Chi Square and Other Hypothesis Test Chi-square test for 1 factor ANOM test for 1 factor Chi-square test for 2 factors Exercise hypothesis tests - shipping Non-parametric tests Analysis: Advanced Control Charts Review of Common Cause and Special Cause Variation Review of the Individuals Control Charts How to calculate Control Limits Four additional tests for Special Causes Control Limits after Process Change Discrete Data Control Charts Control Charts for Discrete Proportion Data Control Charts for Discrete Count Data Control Charts for High Volume Processes with Continuous Data Analysis: Non-Normal Data Test for normal distribution Box-Cox Transformation Box-Cox Transformation for Individuals Control Charts Analysis: Time Series Analysis Introduction to Time Series Analysis Decomposition Smoothing: Moving Average Smoothing: EWMA Analysis: Process Capability Process capability Discrete Data: Defect metrics Discrete Data: Yield metrics Process Capability for Continuous Data: Sigma Value Short- and long-term capabilities Cp, Cpk, Pp, Ppk capability indices Analysis: Measurement System Analysis What is Measurement System Analysis? What defines a good measurement system? Gage R&R Studies Attribute / Discrete Gage R&R Continuous Gage R&R Regression Analysis: Simple Correlation Correlation Coefficient Simple linear regression Checking the fit of the Regression Model Leverage and influence analysis Correlation and regression pitfalls Regression Analysis: Multiple Regression Analysis Introduction to Multiple Regression Multicollinearity Multiple Regression vs. Simple Linear Regression Regression Analysis: Multiple Regression Analysis with Discrete Xs Introduction Creating indicator variables Method 1: Going straight to the intercepts Method 2: Testing for differences in intercepts Logistic Regression: Logistic Regression Introduction to Logistic Regression Logistic Regression - Adding a Discrete X Design of Experiments: Introduction Design of Experiment OFAT experimentation Full factorial design Fractional factorial design DOE road map, hints, and suggestions Design of Experiments: Full Factorial Designs Creating 2k Full Factorial designs in Minitab Randomization Replicates and repetitions Analysis of results: Factorial plots Analysis of results: Factorial design Analysis of results: Fits and Residuals Analysis of results: Response Optimizer Analysis of results: Review Design of Experiments: Pragmatic Approaches Designs with no replication Fractional factorial designs Screening Design of Experiment Case Study Repair Time Blocking Closing: Organizational Change Management Organizational change management Assuring project sponsorship Emphasizing shared need for change Mobilizing stakeholder commitment Closing: Project Management for Lean Six Sigma Introduction to project management Project management for Lean Six Sigma The project baseline plan Work Breakdown Structure (WBS) Resource planning Project budget Project risk Project schedule Project executing Project monitoring and controlling and Closing Closing: Design for Lean Six Sigma Introduction to Design for Lean Six Sigma (DMADV) Introduction to Quality Function Deployment (QFD) Summary and Next Steps IIL's Lean Six Sigma Black Belt Certification Program also prepares you to pass the IASSC Certified Black Belt Exam (optional)

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About this Virtual Instructor Led Training (VILT)  A decision to drill an exploration well with the objective to find a new oil or gas field must be based on sound assessment of the prospect risk and of the volumes. What is the chance that a well will find hydrocarbons, and how much could it be? Risk and volume assessments form the basis for decisions to drill a well or not, and as such form the link between subsurface evaluation and the business aspects of the petroleum industry. This Virtual Instructor Led Training (VILT) course explains how risks and volumes can be assessed in a realistic manner, based on a sound understanding of the geological details of the prospect as well as its regional geological setting and current play understanding. Participants of this VILT course will receive a softcopy of Risk and Volume Assessment Handbook which explains the concepts that are associated with probabilistic Risk & Volume (R & V) Assessment and contains many practical recommendations on how to translate geological understanding into meaningful inputs for probabilistic R &V assessments. The book is fully compatible with any probabilistic R & V tool in the industry. Training Objectives By the end of this VILT course, participants will be able to understand: The fundamentals of risk and volumes assessment; translating geological understanding into reasonable numbers and ranges. The difference between risk and uncertainty. Fundamentals of statistics; including explanation of distribution curves, understanding of expectation curves, do's and don'ts for adding risked volumes, and Bayes theorem. Uncertainty of trap, reservoir, seal and charge, illustrated by examples. Guidelines and exercises for estimating risks realistically and consistently. Calculating volume ranges for prospects and for portfolios of prospects; how to add prospect volumes for a correct representation of prospect portfolios. Incorporation of geophysical evidence (DHIs) in a realistic risk assessment. Target Audience This VILT course has been designed in the first place for geoscientists working in exploration, for prospect portfolio analysts and for their direct supervisors. It will also benefit staff from disciplines working closely with exploration staff, such as reservoir engineers, petrophysicists and geophysicists. Course Level Intermediate Training Methods Learning, methods and tools The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, with 2 breaks of 10 minutes per day. It is the intention to have at least 2 smaller exercises per day. Time will be reserved for recapitulation, questions and discussions. VILT will be conducted either via Zoom or Microsoft Teams. Presenting materials can easily be done on this platform. When participants need to ask a question, they can raise their hand, write notes or interrupt the Instructor by using their microphone. The presenter can switch to a screen where he/she can see all participants (also when each participant is sitting in another location e.g. at home). There is also a whiteboard functionality that can be used as one would use a flip chart. Exercises will be done on an online platform which provides each participant with a private work area that can be accessed by the Instructor to discuss the exercise in a similar manner as in a classroom course. Each topic is introduced by a lecture, and learning is re-enforced by practical exercises and discussions. Handout material in electronic format will be provided. Trainer Dr. Jan de Jager has a PhD in Geology from the University of Utrecht. He joined Shell in 1979 as an exploration geologist, and worked in several locations around the world such as Netherlands, Gabon, USA, Australia, Argentina, and Malaysia in technical and management positions. During the last 10 years of his career, he was responsible for the quality assurance of Shell's exploration prospects in many parts of the world and for upgrading and replenishing Shell's global exploration portfolio. During this period, he had also developed extensive expertise in Prospect Risk and Volume assessments for which he ran successful internal training programmes. Following his retirement from Shell in 2010, Dr Jan de Jager took on a position as part-time professor at the University of Amsterdam and also serves as a consultant exploration advisor for various E&P companies. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Did you know that: An estimated 55% of pregnancies in the UK are planned; the remainder are unplanned or associated with ambivalence1 12% of women aged 15–44 in heterosexual relationships report not using any method of contraception2 NICE guidance (2016) stipulates that women asking for contraception are given information about, and offered a choice of, all methods including long-acting reversible contraception (LARC)2 Over 1/3 of all women in England and Wales have ever an abortion3 Of all woman in England and Wales who had an abortion in 2021, 43% had had a previous abortion4 Why is SHIP training relevant to YOU? Do you worry about how to bring up the topic of contraception out of the blue? Find out how to outline key points about different methods of contraception to patients in a concise and time-efficient way Learn how to assess women to safely reissue combined hormonal contraception, progesterone only pill and injections Do you know what to do if you see a woman has had a recent abortion? Learn quick simple strategies to work out which methods of emergency contraception you should offer women We will help you become confident in bringing up and discussing contraceptive choices and make meaningful changes to your clinical practice! Basic Contraception 1 Differentiate between methods of contraception, including LARCs (long acting reversible contraception) Practice how to bring up contraception & promote LARC appropriately Establish guidelines for re-issuing combined hormonal contraception & progesterone only pill Establish guidelines for administering & re-issuing the contraceptive injection Basic Contraception 2 Manage requests for emergency contraception Outline and practise applying Fraser Guidelines Assess whether a woman is at risk of pregnancy and identify criteria for ‘near patient’ pregnancy testing Understand your role as general practice nurse in abortion referrals & aftercare Each session provides you with up-to-date resources to take back to your practice to support your consultations. References: Wellings K, Jones KG, Mercer CH et al. (2013) The prevalence of unplanned pregnancy and associated factors in Britain: findings from the third National Survey of Sexual Attitudes and Lifestyles (Natsal-3).Lancet 382: 1807–16 NICE Contraception Quality standard Published: 8 September 2016 nice.org.uk/guidance/qs129\ UK Government Abortion statistics, England and Wales https://www.gov.uk/government/statistics/report-on-abortion-statistics-in-england-and-wales-for-2016 Abortion Statistics, England and Wales: 2021, Office for Health Improvement and Disparities https://www.nice.org.uk/sharedlearning/sexual-health-in-practice-training-increases-hiv-testing-in-primary-care Pillay TD, Mullineux J, Smith CJ, et al. Unlocking the potential: longitudinal audit finds multifaceted education for general practice increases HIV testing and diagnosis. Sexually transmitted infections 2013;89(3):191-6. doi: 10.1136/sextrans-2012-050655 Click here to see how SHIP training in Haringey led to increases in testing & changes in practice

Some 60% of injuries at work are caused by lifting heavy objects. This powerful, practical programme is designed to help stop any of your staff from becoming the next statistic. 1 Introduction and objectives 2 Overview of Health and Safety Legislation and HSE Injury Statistics Health and Safety at Work Act 1974 Management of Health and Safety at Work Regulations (MHSWR) 1992 MHSWR 1999 specific duties to risk assess Manual Handling Operations Regulations (MHOR) 1992 Breakdown of injury statistics and costs of poor manual handling 3 The musculoskeletal system explained Prevention and ill-health Ergonomics RSI The spine in detail 4 Risk assessment General principles The TILE method Employees' duties Workplace scenarios

Business Networking 1 Day Training in Buxton

Course Objectives The goal of this course is to provide you with the knowledge required to use more advanced functions and formulas and work with various tools to analyse and present data in spreadsheets, such as sorting, filtering, applying conditional formatting and charting the data. ' Customer Feedback Really useful and engaging course. Learnt a lot that will be very beneficial in my job. Trainer was great. Kelly Moreley - TACT Very happy with the course. Worked as a good refresher from what I knew already and enhanced my knowledge further in formulas + vlookup and shortcut keys. Jenny Price - Acer 1 year email support service Take a look at the consistent excellent feedback from our corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke courses. Tailored training courses: In, in company training, you can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Recap on Excel formulas and calculations Overview of formulas in Excel Relative, Absolute and Mixed cell references Group editing worksheets Autofill and Flash Fill Changing Excel’s environment Options Changing the default number of sheets Creating an Autofill Custom List Adding tools to the Quick Access Toolbar Mastering Excel Tables Introducing Excel Tables Formatting a Table Creating Calculated Columns Using Slicers to filter your data Using Totals to get statistics out of your data Removing duplicates Converting Tables back to normal Ranges Using names Ranges In Excel formulas As a way of navigating through the workbook Advanced Formulas Simple IF examples Using IF to check if a cell is blank Nested IFs VLOOKUP HLOOKUP Text Functions Date Functions Conditional formatting Apply Conditional Formatting Customising Conditional Formatting Using Icons in Conditional Formatting Using Formulas to conditionally format cells Linking spreadsheets and workbooks Making a reference to another worksheet Making a reference to another workbook Editing links Troubleshooting links Analysing databases Quick analysis Sorting a database Apply filters to a database Advance filter Sorting and Filtering by Conditional Formats Charts Analyse trends in data using Sparklines Creating charts from start to finish Exploring the different Chart Types Apply Chart Styles Formatting Chart Elements Filtering Charts by Series or Categories Adding a Trendline to a Chart Create a Chart Template Attaching security to a spreadsheet and workbook Protect Cells Protect Structure of worksheets Protect a Workbook by adding passwords Introduction to Pivot Tables What are Pivot Tables? Using recommended pivot tables to analyse your data Who is this course for? Who is this course for? For those who want to explore in more detail formulas and functions, data analysis and data presentation. Requirements Requirements Preferably, delegates would have attended the Excel Introduction course. Career path Career path Excel know-how can instantly increase your job prospects as well as your salary. 80 percent of job openings require spreadsheet and word-processing software skills Certificates Certificates Certificate of completion Digital certificate - Included

Python Data Analytics boot camp. 12 1 day lessons, learn Python Basics through to machine learning and front-ends. With practical project to give you full confidence and credibility.