1137 Statistics courses

Duration 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Total NetFlow training course description A comprehensive hands on course covering NetFlow. The course starts with the basics of flows moving swiftly onto configuring NetFlow and studying the information it provides. What will you learn Describe NetFlow. Configure generators and collectors. Recognise how NetFlow can be used. Describe the issues in using NetFlow. Compare NetFlow with SNMP, RMON and sflow. Total NetFlow training course details Who will benefit: Technical staff working with NetFlow. Prerequisites: TCP/IP Foundation Duration 2 days Total NetFlow for engineers What is NetFlow? Flows. Where to monitor traffic. Hands on Wireshark flow analysis. Getting started with NetFlow NetFlow configuration. Hands on Accessing NetFlow data using the CLI. NetFlow architecture Generators and collectors. When flows are exported. NetFlow reporting products. SolarWinds. Hands on Collector software. NetFlow features and benefits Real time segment statistics, real time top talkers, traffic matrices. Hands on Traffic analysis with NetFlow. NetFlow issues NetFlow impact, agent resources, server resources, comparing NetFlow with SNMP, RMON and sflow. Hands on Advanced NetFlow configuration. Export formats Flow aging timers, NetFlow versions, export formats, templates, IPFIX. Hands on NetFlow packet analysis. NetFlow MIBs The NetFlow MIB, configuration, retrieving NetFlow statistics. Hands on Integrating NetFlow with SNMP.

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WCNA training course description Wireshark is a free network protocol analyser. This hands-on course provides a comprehensive tour of using Wireshark to troubleshoot networks. The course concentrates on the information needed in order to pass the WCNA exam. Students will gain the most from this course only if they already have a sound knowledge of the TCP/IP protocols. What will you learn Analyse packets and protocols in detail. Troubleshoot networks using Wireshark. Find performance problems using Wireshark. Perform network forensics. WCNA training course details Who will benefit: Technical staff looking after networks. Prerequisites: TCP/IP Foundation for engineers Duration 5 days WCNA training course contents What is Wireshark? Network analysis, troubleshooting, network traffic flows. Hands on Download/install Wireshark. Wireshark introduction Capturing packets, libpcap, winpcap, airpcap. Dissectors and plugins. The menus. Right click. Hands on Using Wireshark. Capturing traffic Wireshark and switches and routers. Remote traffic capture. Hands on Capturing packets. Capture filters Applying, identifiers, qualifiers, protocols, addresses, byte values. File sets, ring buffers. Hands on Capture filters. Preferences Configuration folders. Global and personal configurations. Capture preferences, name resolution, protocol settings. Colouring traffic. Profiles. Hands on Customising Wireshark. Time Packet time, timestamps, packet arrival times, delays, traffic rates, packets sizes, overall bytes. Hands on Measuring high latency. Trace file statistics Protocols and applications, conversations, packet lengths, destinations, protocol usages, strams, flows. Hands on Wireshark statistics. Display filters Applying, clearing, expressions, right click, conversations, endpoints, protocols, combining filters, specific bytes, regex filters. Hands on Display traffic. Streams Traffic reassembly, UDP and TCP conversations, SSL. Hands on Recreating streams. Saving Filtered, marked and ranges. Hands on Export. TCP/IP Analysis The expert system. DNS, ARP, IPv4, IPv6, ICMP, UDP, TCP. Hands on Analysing traffic. IO rates and trends Basic graphs, Advanced IO graphs. Round Trip Time, throughput rates. Hands on Graphs. Application analysis DHCP, HTTP, FTP, SMTP. Hands on Analysing application traffic. WiFi Signal strength and interference, monitor mode and promiscuous mode. Data, management and control frames. Hands on WLAN traffic. VoIP Call flows, Jitter, packet loss. RTP, SIP. Hands on Playing back calls. Performance problems Baselining. High latency, arrival times, delta times. Hands on Identifying poor performance. Network forensics Host vs network forensics, unusual traffic patterns, detecting scans and sweeps, suspect traffic. Hands on Signatures. Command line tools Tshark, capinfos, editcap, mergecap, text2pcap, dumpcap. Hands on Command tools.

Total SIPp course description SIPp is a robust performance testing tool designed for evaluating the SIP protocol. This comprehensive course takes you on a journey from the initial installation of SIPp to mastering fundamental scenarios, exploring diverse architectures, delving into statistics analysis, and crafting XML scenario files. What will you learn Monitor SIP traffic with SIPp. Use SIPp for performance testing. Use the standard SIPp scenarios. Create custom scenarios in XML for SIPp. Total SIPp course details Who will benefit: Those working with SIP. Prerequisites: Definitive SIP for engineers Duration 2 days Total SIPp course contents Introduction What is SIPp? SIP review: UAC, UAS, INVITE, BYE. Sample SIP call flows. Hands on Wireshark, SIP call flow. Installing SIPp Getting SIPp, installing SIPp. Using SIPp Running sipp. sipp with uas scenario, sipp with uac scenario. The integrated scenarios. Online help. Hands on uac, uas. Controlling SIPp Hot keys, commands, UDP socket. Running SIPp in the background. Traffic control. SIPp performance testing. Hands on Changing call rates, remote control, pausing traffic. Monitoring SIP traffic Scenario screen, statistics. Response times, counters. Hands on Monitoring SIP traffic. More integrated scenarios SIPp and media and RTP. 3PCC. 3PCC extended. Transport modes: UDP, TCP, TLS, SCTP, IPv6 mono and multi socket. Hands on Third Party Call Control. XML What is XML? Content, markup, elements, attributes. Start tags, end tags. Hands on Displaying embedded scenarios, looking at the XML files of the integrated scenarios. Creating your own XML scenarios scenario, message commands, send, recv, nop, pause, sendCmd, recvCmd, common sipp scenario attributes, command specific sipp scenario attributes. XML DTD, jEdit. Hands on uac and uas scenario XML files. Recv actions Log and warning, exec, variables, variable types, variable scope. External variables. Hands on RTP streaming, Change a calls network destination, injection files. Regular expressions What is an RE. POSIX 1003.2. Re injection. Validation. Hands on regex example.

Lean Six Sigma Green Belt Certification Program: In-House Training This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

Lean Six Sigma Green Belt Certification Program This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps

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Lean Six Sigma Green Belt Certification Program: Virtual In-House Training This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. With a real-world project focus, the series will teach the fundamental methodology, tools, and techniques of the Define, Measure, Analyze, Improve and Control Process Improvement Methodology. This course is delivered through sixteen 3-hour online sessions. What you Will Learn At the end of this program, you will be able to: Identify strategies for effectively leading high performing process improvement teams Analyze whether projects align with business strategy Apply process improvement methodologies to DMAIC steps, based on real world scenarios Explain ways to appropriately respond to process variation Distinguish among best practice problem solving methodologies Evaluate and effectively communicate data-driven decisions, based on real world scenarios Introduction Lean Six Sigma & quality The vision The methodologies The metric Project Selection Why Projects Random idea generation Targeted idea generation CTQs (Critical to Quality) & projects Project screening criteria Quick improvements Introduction to Define Project Planning Developing the core charter Developing a project charter Facilitation Process Management Business process management Top-down process mapping Voice of the Customer Voice of Customer Stakeholder analysis Communication planning Kicking off the project Define Summary Introduction to Measure Data Collection Fact-based decision making Data sampling Operations definitions Data collection plan Measurement system analysis Graphical Statistics for Continuous Data Meet Six SigmaXL Graphical & statistical tools Data stratification Graphical Statistics for Discrete Data Pareto analysis Dot plots Plotting data over time: Looking for patterns Variation Concepts Variation is reality Special Cause and Common Cause variation Example of standard business reporting Individuals Control Chart Process Capability Genesis of process capability Calculating the metrics of Six Sigma Yield metrics: Measuring process efficiency Cost of Poor Quality The Cost of Poor Quality (COPQ) Cost of Quality categories Calculating the Cost of Poor Quality Measure Summary Introduction to Analyze Process Analysis Introduction to process analysis Value-added analysis Cycle time analysis WIP & pull systems Analyzing bottlenecks and constraints Cause & Effect Analysis Fishbone/Ishikawa diagram 5-Whys analysis Graphical & statistical tools Advanced Analysis Why use hypothesis rests? Hypothesis tests Correlation and regression analysis Analyze Summary Introduction to Improve Solutions Creativity techniques Generating alternative solutions Solution selection techniques Introduction to Design of Experiments Introduction to DOE DOE activity Error Proofing Failure mode & effect analysis Poka-Yoke Project Management Fundamentals Successful teams Project roles Conflict management Standardization Standardization The Visual Workplace 5S Piloting & Verifying Results What is a pilot? Evaluating results Improve Summary Introduction to Control Statistical Process Control Review of Special & Common Cause variation Review of Individual Control Chart P-Chart for discrete proportion data Transition Planning Control plan Project closure Control Summary Summary and Next Steps