7 SPSS courses

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.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for information workers and data science professionals who seek to use database reporting and analysis tools such as Microsoft SQL Server Reporting Services, Excel, Power BI, R, SAS and other business intelligence tools, and wish to use TSQL queries to efficiently retrieve data sets from Microsoft SQL Server relational databases for use with these tools. Overview After completing this course, students will be able to: - Identify independent and dependent variables and measurement levels in their own analytical work scenarios. - Identify variables of interest in relational database tables. - Choose a data aggregation level and data set design appropriate for the intended analysis and tool. - Use TSQL SELECT queries to produce ready-to-use data sets for analysis in tools such as PowerBI, SQL Server Reporting Services, Excel, R, SAS, SPSS, and others. - Create stored procedures, views, and functions to modularize data retrieval code. This course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. 1 - INTRODUCTION TO TSQL FOR BUSINESS INTELLIGENCE * Two Approaches to SQL Programming * TSQL Data Retrieval in an Analytics / Business Intelligence Environment * The Database Engine * SQL Server Management Studio and the CarDeal Sample Database * Identifying Variables in Tables * SQL is a Declarative Language * Introduction to the SELECT Query * Lab 1: Introduction to TSQL for Business Intelligence 2 - TURNING TABLE COLUMNS INTO VARIABLES FOR ANALYSIS: SELECT LIST EXPRESSIONS, WHERE, AND ORDER BY * Turning Columns into Variables for Analysis * Column Expressions, Data Types, and Built-in Functions * Column aliases * Data type conversions * Built-in Scalar Functions * Table Aliases * The WHERE clause * ORDER BY * Lab 1: Write queries 3 - COMBINING COLUMNS FROM MULTIPLE TABLES INTO A SINGLE DATASET: THE JOIN OPERATORS * Primary Keys, Foreign Keys, and Joins * Understanding Joins, Part 1: CROSS JOIN and the Full Cartesian Product * Understanding Joins, Part 2: The INNER JOIN * Understanding Joins, Part 3: The OUTER JOINS * Understanding Joins, Part 4: Joining more than two tables * Understanding Joins, Part 5: Combining INNER and OUTER JOINs * Combining JOIN Operations with WHERE and ORDER BY * Lab 1: Write SELECT queries 4 - CREATING AN APPROPRIATE AGGREGATION LEVEL USING GROUP BY * Identifying required aggregation level and granularity * Aggregate Functions * GROUP BY * HAVING * Order of operations in SELECT queries * Lab 1: Write queries 5 - SUBQUERIES, DERIVED TABLES AND COMMON TABLE EXPRESSIONS * Non-correlated and correlated subqueries * Derived tables * Common table expressions * Lab 1: Write queries 6 - ENCAPSULATING DATA RETRIEVAL LOGIC * Views * Table-valued functions * Stored procedures * Creating objects for read-access users * Creating database accounts for analytical client tools * Lab 1: Encapsulating Data Retrieval Logic 7 - GETTING YOUR DATASET TO THE CLIENT * Connecting to SQL Server and Submitting Queries from Client Tools * Connecting and running SELECT queries from: * Excel * PowerBI * RStudio * Exporting datasets to files using * Results pane from SSMS * The bcp utility * The Import/Export Wizard * Lab 1: Getting Your Dataset to the Client ADDITIONAL COURSE DETAILS: Nexus Humans 55232 Writing Analytical Queries for Business Intelligence 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 55232 Writing Analytical Queries for Business Intelligence 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 3 Days 18 CPD hours This course is intended for This course is intended for information workers and data science professionals who seek to use database reporting and analysis tools such as Microsoft SQL Server Reporting Services, Excel, Power BI, R, SAS and other business intelligence tools, and wish to use TSQL queries to efficiently retrieve data sets from Microsoft SQL Server relational databases for use with these tools. Overview Identify independent and dependent variables and measurement levels in their own analytical work scenarios. Identify variables of interest in relational database tables. Choose a data aggregation level and data set design appropriate for the intended analysis and tool. Use TSQL SELECT queries to produce ready-to-use data sets for analysis in tools such as PowerBI, SQL Server Reporting Services, Excel, R, SAS, SPSS, and others. Create stored procedures, views, and functions to modularize data retrieval code. This three-day instructor-led course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. Specifically, this course presents TSQL within the context of data analysis in other words, making meaning from the data rather than transaction-oriented data-tier application development. The course starts with a brief discussion of levels of measurement and quantitative research methodogy, and integrates these concepts into each TSQL topic presented. The goal is to provide a consistent, direct, and purposeful learning path from RDBMS data retrieval through analytical tools such as SQL Server Reporting Services, PowerBI, Excel, R, SAS, and SPSS. MODULE 1: INTRODUCTION TO TSQL FOR BUSINESS INTELLIGENCE * Two Approaches to SQL Programming * TSQL Data Retrieval in an Analytics / Business Intelligence Environment * The Database Engine * SQL Server Management Studio and the CarDeal Sample Database * Identifying Variables in Tables * SQL is a Declarative Language * Introduction to the SELECT Query MODULE 2: TURNING TABLE COLUMNS INTO VARIABLES FOR ANALYSIS: SELECT LIST EXPRESSIONS, WHERE, AND ORDER BY * Turning Columns into Variables for Analysis * Column Expressions, Data Types, and Built-in Functions * Column aliases * Data type conversions * Built-in Scalar Functions * Table Aliases * The WHERE clause * ORDER BY MODULE 3: COMBINING COLUMNS FROM MULTIPLE TABLES INTO A SINGLE DATASET: THE JOIN OPERATORS * Primary Keys, Foreign Keys, and Joins * Understanding Joins, Part 1: CROSSJOIN and the Full Cartesian Product * Understanding Joins, Part 2: The INNERJOIN * Understanding Joins, Part 3: The OUTERJOINS * Understanding Joins, Part 4: Joining more than two tables * Understanding Joins, Part 5: Combining INNER and OUTERJOINs * Combining JOIN Operations with WHERE and ORDER BY MODULE 4: CREATING AN APPROPRIATE AGGREGATION LEVEL USING GROUP BY * Identifying required aggregation level and granularity * Aggregate Functions * GROUP BY * HAVING * Order of operations in SELECT queries MODULE 5: SUBQUERIES, DERIVED TABLES AND COMMON TABLE EXPRESSIONS * Non-correlated and correlated subqueries * Derived tables * Common table expressions * MODULE 6: ENCAPSULATING DATA RETRIEVAL LOGIC * Views * Table-valued functions * Stored procedures * Creating objects for read-access users * Creating database accounts for analytical client tools MODULE 7: GETTING YOUR DATASET TO THE CLIENT * Connecting to SQL Server and Submitting Queries from Client Tools * Connecting and running SELECT queries from: * Excel * PowerBI * RStudio * Exporting datasets to files using * Results pane from SSMS * The bcp utility * The Import/Export Wizard ADDITIONAL COURSE DETAILS: Nexus Humans Writing Analytical Queries for Business Intelligence 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 Writing Analytical Queries for Business Intelligence 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.

ABOUT COURSE MASTER THE STATISTICAL SKILLS YOU NEED TO UNDERSTAND AND ANALYZE BIOMEDICAL RESEARCH DATA WITH THIS BIOSTATISTICS ONLINE COURSE Are you working on public health, clinical medicine, biology or related fields? Are you familiar with the process of obtaining an accurate picture from a large number of data points? This Biostatistics Online Course demonstrates how to use statistical techniques to summarize the characteristics of a data set to draw meaningful conclusions. In this course, you will learn all about Biostatistics and its application in medical and life sciences. This course is a comprehensive introduction to the field of biostatistics, covering a wide range of topics from basic statistical concepts to more advanced biostatistical methods. BIOSTATISTICS ONLINE COURSE MODULES: * MODULE 1: INTRODUCTION TO BIOSTATISTICS This module provides an overview of biostatistics, its applications in the field of health sciences, and the different types of study designs used in biomedical research. It also introduces the basic concepts of statistics, including data types, variables, inferential statistics, hypothesis testing, and the role of statistics in biostatistics and evidence-based medicine. * MODULE 2: PROBABILITY This module covers the basics of probability, including probability distributions, random variables, and sampling distributions. Students will learn how to calculate and interpret probabilities in the context of biomedical research. * MODULE 3: DESCRIPTIVE STATISTICS This module covers the different measures of central tendency and variability, as well as graphical representations of data. Students will learn how to describe and summarize data from biomedical studies using these methods. * MODULE 4: INFERENTIAL STATISTICS This module covers the fundamental concepts of inferential statistics, including estimation, hypothesis testing, confidence intervals, and p-values. Students will learn how to use these methods to draw conclusions about populations based on data from samples. * MODULE 5: REGRESSION ANALYSIS This module introduces the basics of regression analysis, including simple linear regression, multiple linear regression, and logistic regression. Students will learn how to use these methods to model relationships between variables and to make predictions. * Module 6: Biostatistics Tools This module covers a variety of biostatistical tools that are commonly used in biomedical research, including survival analysis, clinical trials, and epidemiological studies. Students will learn how to use these tools to answer specific research questions. * MODULE 7: STATISTICAL SOFTWARE AND TOOLS This module introduces students to popular statistical software programs, such as R and SPSS. Students will learn how to import, manage, and analyze data using these software programs, as well as how to perform statistical tests and generate summary statistics. * MODULE 8: ETHICAL CONSIDERATIONS AND REPORTING GUIDELINES This module covers the importance of ethical considerations in biostatistics and the reporting guidelines for statistical analysis in research publications. Students will also learn about best practices for data management and data sharing.   Why You Should Take This Course Whether you are a student, researcher, or healthcare professional, biostatistics is an essential skill for understanding and interpreting biomedical research. This course provides a comprehensive and accessible introduction to the field of biostatistics, covering all the essential topics that you need to know. By taking this course, you will learn how to: * Design and conduct biomedical studies * Collect and manage data * Analyze data using statistical methods * Interpret statistical results * Communicate statistical findings effectively This course is ideal for students in the fields of public health, medicine, nursing, epidemiology, and other health sciences. It is also beneficial for researchers, healthcare professionals, and anyone else who wants to learn more about biostatistics.   Enroll today and start your journey to becoming a biostatistics expert!   To find more course in this topic, search more . WHAT WILL YOU LEARN? * Design and conduct biomedical studies * Collect and manage data * Analyze data using statistical methods * Interpret statistical results * Communicate statistical findings effectively COURSE CONTENT INTRODUCTION TO BIOSTATISTICS * INTRODUCTION TO BIOSTATISTICS PROBABILITY * MODULE 2 PROBABILITY DESCRIPTIVE STATISTICS * DESCRIPTIVE STATISTICS INFERENTIAL STATISTICS * INFERENTIAL STATISTICS REGRESSION ANALYSIS * REGRESSION ANALYSIS BIOSTATISTICS TOOLS * BIOSTATISTICS TOOLS STATISTICAL SOFTWARE AND TOOLS * STATISTICAL SOFTWARE AND TOOLS ETHICAL CONSIDERATIONS AND REPORTING GUIDELINES * ETHICAL CONSIDERATIONS AND REPORTING GUIDELINES A course by Xpert Learning RequirementsBasic understanding of Mathematics and Statistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics AUDIENCE * Students in health sciences * Researchers * Healthcare professionals * Anyone interested in learning about biostatistics

This course is perfect for the beginner but also delves into building a SAS Model and intermediate topics. Learn SAS Data Step, SQL Step, Macros, SAS Model Building, Predictive Analytics, SAS and ML. If you are using SAS Enterprise Guide and want to learn how to code/program instead of using the point-and-click interface, this course is ideal!