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Duration 2 Days 12 CPD hours This course is intended for New users of IBM SPSS Statistics Users who want to refresh their knowledge about IBM SPSS Statistics Anyone who is considering purchasing IBM SPSS Statistics Overview Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables. Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders Additional course details: Nexus Humans 0G53BG IBM SPSS Statistics Essentials (V26) 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 0G53BG IBM SPSS Statistics Essentials (V26) 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.

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

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.

Wireshark 101 training course description Wireshark is a free network protocol analyser. This hands-on course focuses on troubleshooting networks using the Wireshark protocol analyser. The course concentrates on the product and students will gain from the most from this course only if they already have a sound knowledge of the TCP/IP protocols What will you learn Download and install Wireshark. Capture and analyse packets with Wireshark. Configure capture and display filters. Customise Wireshark. Troubleshoot networks using Wireshark. Wireshark 101 training course details Who will benefit: Technical staff looking after networks. Prerequisites: TCP/IP Foundation for engineers Duration 2 days Wireshark 101 training course contents What is Wireshark? Protocol analysers, Wireshark features, versions, troubleshooting techniques with Wireshark. Installing Wireshark Downloading Wireshark, UNIX issues, Microsoft issues, the role of winpcap, promiscuous mode, installing Wireshark. Wireshark documentation and help. Hands on Downloading and installing Wireshark. Capturing traffic Starting and stopping basic packet captures, the packet list pane, packet details pane, packet bytes pane, interfaces, using Wireshark in a switched architecture. Hands on Capturing packets with Wireshark. Troubleshooting networks with Wireshark Common packet flows. Hands on Analysing a variety of problems with Wireshark. Capture filters Capture filter expressions, capture filter examples (host, port, network, protocol), primitives, combining primitives, payload matching. Hands on Configuring capture filters. Working with captured packets Live packet capture, saving to a file, capture file formats, reading capture files from other analysers, merging capture files, finding packets, going to a specific packet, display filters, display filter expressions. Hands on Saving captured data, configuring display filters. Analysis and statistics with Wireshark Enabling/disabling protocols, user specified decodes, following TCP streams, protocol statistics, conversation lists, endpoint lists, I/O graphs, protocol specific statistics. Hands on Using the analysis and statistics menus. Command line tools Tshark, capinfos, editcap, mergecap, text2pcap, idl2eth. Hands on Using tshark. Advanced issues 802.11 issues, management frames, monitor mode, packet reassembling, name resolution, customising Wireshark. Hands on Customising name resolution.

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.