

Statistics Training Courses and WorkshopsSchools providing training courses, certificates, diplomas or degree programs of Statistics
Total 578 training courses and degree programs available around the world.
United States  United Kingdom  Canada  Australia  India
Popular courses:
Statistics
Business Statistics
Biostatistics
Applied Statistics
Survey Analysis Using IBM SPSS Statistics
Data Management and Manipulation with IBM SPSS Statistics
StatisticsCourse Format: Online School/Trainer: Anne Arundel Community College Training Center(s)/Venue(s): Annapolis, Arnold, Baltimore, Edgewater, Gambrills, Hanover, Laurel, Severn, United States VUse meaningful data to explore concepts in probability and statistics including measures of central tendency and dispersion. Develop statistical literacy by studying graphical representations of data, discrete and continuous probability distributions, and sampling techniques and theory. Construct and interpret confidence intervals, find lines of bestfit, and perform hypothesis tests for means, proportions, and independence. Technology use is required throughout the course for statistical analyses.
Business StatisticsCourse Format: Online School/Trainer: Anne Arundel Community College Training Center(s)/Venue(s): Annapolis, Arnold, Baltimore, Edgewater, Gambrills, Hanover, Laurel, Severn, United StatesLearn statistical analysis as an aid in business decision making through the use of descriptive statistics, probability, confidence intervals, hypothesis testing, chi square, analysis of variance, regression and correlation analysis.
Financial Data/Statistics ManagementCourse Format: Classroom School/Trainer: Globe University  Wisconsin Training Center(s)/Venue(s): Appleton, Eau Claire, La Crosse, Madison, Wausau, United StatesStudents will investigate information technology solutions used to manage financial data/statistics and their applications. Research topics include qualitative and quantitative approaches, validity and reliability testing, and related practices.
Financial Data/Statistics ManagementCourse Format: Classroom School/Trainer: Globe University Sioux Falls Campus Training Center(s)/Venue(s): Sioux Falls, United StatesStudents will investigate information technology solutions used to manage financial data/statistics and their applications. Research topics include qualitative and quantitative approaches, validity and reliability testing, and related practices.
Financial Data/Statistics ManagementCourse Format: Classroom School/Trainer: Minnesota School of Business & Globe University Training Center(s)/Venue(s): Blaine, Minneapolis, Richfield, Rochester, Woodbury, United StatesStudents will investigate information technology solutions used to manage financial data/statistics and their applications. Research topics include qualitative and quantitative approaches, validity and reliability testing, and related practices.
SAS Visual Statistics: Interactive Model BuildingCourse Format: Classroom School/Trainer: Global Knowledge USA Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VIn this course, you will learn about SAS Visual Statistics for building predictive models in an interactive, exploratory way. Exploratory model fitting is a critical step in modeling big data.
Who Needs To Attend
Predictive modelers Business analysts Data scientists who want to take advantage of SAS Visual Statistics for highly interactive, rapid model fitting
Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression (Certificate)Course Format: Classroom School/Trainer: Global Knowledge USA Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VThis course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on ttests, ANOVA, linear regression, and logistic regression. This course (or equivalent knowledge) is a prerequisite to many of the courses in the statistical analysis curriculum.
Certification: SAS Certified Clinical Trials Programmer Using SAS 9 SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
Survey Analysis Using IBM SPSS StatisticsCourse Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VThis course reviews the standard methods that are used to analyze survey data, beginning with simple methods, such as crosstabulations, and moving toward the advanced, such as logistic regression. Appropriate methods of analysis are discussed for both categorical and continuous data. Also included are discussions of qualitative data analysis and the reporting and presentation of survey results.
Course Content ## The Logic of Survey Analysis ## Data checking and data validation ## Data transformations: create new variables ## Testing for Reliability and Validity ## Analyzing Categorical Variables ## Analyzing Interval Variables ## Analyzing Text Data ## Reporting Survey Results for Categorical and Scale Data ## Clustering Respondents ## Multivariate Analysis using Regression Techniques ## Special Issues: Missing Data ## Special Issues: Complex Samples and Sample Weights ## Measuring Change over Time with Surveys ## Decision Tree Analysis
Statistical Analysis Using IBM SPSS StatisticsCourse Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VIntroduction to Statistical Analysis Explain the difference between a sample and a population Explain the difference between an experimental research design and a nonexperimental research design Explain the difference between independent and dependent variables
Examine Individual Variables Describe the levels of measurement used in IBM SPSS Statistics Use graphs to examine variables Use summary measures to examine variables Explain normal distributions Explain standardized scores and their use
Test HypothesesTheory Explain the difference between a sample and a population Design a test of a hypothesis Explain the alpha level Explain the difference between statistical and practical significance Describe the two types of errors in testing a hypothesis
Test Hypotheses about Individual Variables Explain the sampling distribution of a statistic Explain the difference between the standard deviation and the standard error Use the OneSample T Test to test a hypothesis about a population mean Use the PairedSamples T Test to test on an &,quot,&,quot,before... [Read More]
IBM SPSS StatisticsCourse Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VIntroduction to IBM SPSS Statistics (V23) guides you through the fundamentals of using IBM SPSS Statistics for typical data analysis process. You will learn the basics of reading data, data definition, data modification, and data analysis and presentation of analytical results. You will also see how easy it is to get data into IBM SPSS Statistics so that you can focus on analyzing the information. In addition to the fundamentals, you will learn shortcuts that will help you save time. This course uses the IBM SPSS Statistics Base features.
IBM SPSS Statistics: Exploratory Data Analysis V19Course Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States Va one day instructorled online course that provides a practical, applicationoriented introduction to some of the advanced statistical methods available in IBM®SPSS® Statistics for data analysts and researchers. Students will review several 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, as well as how to interpret the results. Students will gain an understanding of when and why to use these various techniques as well as how to apply them with confidence and interpret their output.
Factor Analysis ## Explain the basic theory of factor analysis and the steps in factor analysis ## Explain the assumptions and requirements of factor analysis ## Specify a factor analysis and interpret the output
KMeans Cluster Analysis ## Explain the basic theory of cluster analysis and the steps in doing a cluster analysis ## Explain the approach of KMeans cluster analysis ## Specify a KMeans cluster analysis and interpret the output
TwoStep Cluster Analysis ## Explain the basic approach of TwoStep cluster analys... [Read More]
IBM SPSS Statistics SyntaxCourse Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VSyntax is the command language that gives instructions to SPSS Statistics on how to modify, manage, and analyze your data. Syntax programs can be used to automate repetitive tasks and perform additional options that are not available in the dialog boxes. You will learn the rules of SPSS syntax, how to generate syntax from the dialog boxes, modify and optimize its use. The approach of the course will be that the dialog boxes and syntax are complementary.
Course Content ## Why Syntax? ## Working with Syntax ## Generating Syntax from the GUI ## The Syntax Editor ## Managing Syntax (e.g., log syntax in the Viewer and/or a journal file, Insert syntax from file)
## Syntax for Reading and Saving Data (e.g. for reading and saving SPSS Statistics data files, ExcelTM files, text files) ## Syntax for Defining Variables (e.g. variable and value labels, missing values) ## Syntax for Selecting Cases (e.g. filtering cases, copying selected to new dataset) ## Syntax for Transformations (e.g. Compute, Visual Binning, Recode)
Data Management and Manipulation with IBM SPSS StatisticsCourse Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VHelpful Data Management Features Read from a database using the Database Wizard Customize variable attributes Compare datasets Use Variable Sets Rename datasets
Use Functions Identify the general form of a function Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables
Additional Data Transformations Use Automatic Recode to recode string variables into numeric variables Use Count Values within Cases to count values across variables
Set the Unit of Analysis Remove duplicate cases Create aggregated datasets Restructure datasets
Merge Files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information
Analyze Multiple Response Questions Describe the two ways to encode a multiple response set Define multiple response sets Use the Multiple Response Frequencies and Crosstabs procedures
Edit Tables and Charts Use the features of the Pivot Table Editor Create and apply ... [Read More]
Advanced Statistical Analysis Using IBM SPSS Statistics (V19)Course Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VFactor Analysis ## Explain the basic theory of factor analysis and the steps in factor analysis ## Explain the assumptions and requirements of factor analysis ## Specify a factor analysis and interpret the output
KMeans Cluster Analysis ## Explain the basic theory of cluster analysis and the steps in doing a cluster analysis ## Explain the approach of KMeans cluster analysis ## Specify a KMeans cluster analysis and interpret the output
TwoStep Cluster Analysis ## Explain the basic approach of TwoStep cluster analysis ## Specify a TwoStep cluster analysis ## Use the Model Viewer to study and interpret the output
Binary Logistic Regression ## Explain the basic theory and assumptions of logistic regression ## Specify a logistic regression analysis ## Interpret model fit, logistic regression coefficients and model accuracy
Multinomial Logistic Regression ## Explain the basic theory of multinomial logistic regression ## Specify a multinomial logistic regression analysis ## Interpret model fit, logistic regression coefficients and model accuracy
D... [Read More]
IBM Cognos Statistics: Author Statistical Reports in Report StudioCourse Format: Classroom School/Trainer: Global Knowledge USA IBM Training Centers Training Center(s)/Venue(s): Arlington, Atlanta, Cary, Irving, Morristown, New York City, Santa Clara, Schaumburg, Seattle, United States VIntroduction to IBM Cognos Statistics Explain what IBM Cognos Statistics is Explain the architecture of IBM Cognos Statistics Explain data types used in IBM Cognos Statistics Explain the use of the case variable in statistical objects
Examine Descriptive Statistical Reports Compare descriptive statistics and inferential statistics Examine descriptive statistics (mean, count, minimum, maximum, standard deviation)
Examine Data Distribution with Statistical Charts Explain histograms and normal distribution curves Explain boxplots Explain grouping variables Explain normality tests using QQ plot
Examine Curve Estimation, Correlation and Regression Compare categorical data and numeric data Explain statistical significance Explain hypothesis testing Demonstrate the relationship between two variables using basic correlation Explain linear and logarithmic curves in curve estimation Explain regression coefficients
Examine the Means Comparison Tests Explore a onesample ttest Examine the oneway ANOVA technique
Examine Nonparametric Tests... [Read More]
Survey Analysis Using IBM SPSS StatisticsCourse Format: Classroom School/Trainer: Global Knowledge Canada IBM Training Centres Training Center(s)/Venue(s): Halifax, Mississauga, Montreal, Ottawa, Toronto, Winnipeg, Canada VThis course reviews the standard methods that are used to analyze survey data, beginning with simple methods, such as crosstabulations, and moving toward the advanced, such as logistic regression. Appropriate methods of analysis are discussed for both categorical and continuous data. Also included are discussions of qualitative data analysis and the reporting and presentation of survey results.
Course Content ## The Logic of Survey Analysis ## Data checking and data validation ## Data transformations: create new variables ## Testing for Reliability and Validity ## Analyzing Categorical Variables ## Analyzing Interval Variables ## Analyzing Text Data ## Reporting Survey Results for Categorical and Scale Data ## Clustering Respondents ## Multivariate Analysis using Regression Techniques ## Special Issues: Missing Data ## Special Issues: Complex Samples and Sample Weights ## Measuring Change over Time with Surveys ## Decision Tree Analysis
Statistical Analysis Using IBM SPSS StatisticsCourse Format: Classroom School/Trainer: Global Knowledge Canada IBM Training Centres Training Center(s)/Venue(s): Halifax, Mississauga, Montreal, Ottawa, Toronto, Winnipeg, Canada VIntroduction to Statistical Analysis Explain the difference between a sample and a population Explain the difference between an experimental research design and a nonexperimental research design Explain the difference between independent and dependent variables
Examine Individual Variables Describe the levels of measurement used in IBM SPSS Statistics Use graphs to examine variables Use summary measures to examine variables Explain normal distributions Explain standardized scores and their use
Test HypothesesTheory Explain the difference between a sample and a population Design a test of a hypothesis Explain the alpha level Explain the difference between statistical and practical significance Describe the two types of errors in testing a hypothesis
Test Hypotheses about Individual Variables Explain the sampling distribution of a statistic Explain the difference between the standard deviation and the standard error Use the OneSample T Test to test a hypothesis about a population mean Use the PairedSamples T Test to test on an &,quot,&,quot,before... [Read More]
IBM SPSS StatisticsCourse Format: Classroom School/Trainer: Global Knowledge Canada IBM Training Centres Training Center(s)/Venue(s): Halifax, Mississauga, Montreal, Ottawa, Toronto, Winnipeg, Canada VIntroduction to IBM SPSS Statistics (V23) guides you through the fundamentals of using IBM SPSS Statistics for typical data analysis process. You will learn the basics of reading data, data definition, data modification, and data analysis and presentation of analytical results. You will also see how easy it is to get data into IBM SPSS Statistics so that you can focus on analyzing the information. In addition to the fundamentals, you will learn shortcuts that will help you save time. This course uses the IBM SPSS Statistics Base features.
IBM SPSS Statistics: Exploratory Data Analysis V19Course Format: Classroom School/Trainer: Global Knowledge Canada IBM Training Centres Training Center(s)/Venue(s): Halifax, Mississauga, Montreal, Ottawa, Toronto, Winnipeg, Canada Va one day instructorled online course that provides a practical, applicationoriented introduction to some of the advanced statistical methods available in IBM®SPSS® Statistics for data analysts and researchers. Students will review several 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, as well as how to interpret the results. Students will gain an understanding of when and why to use these various techniques as well as how to apply them with confidence and interpret their output.
Factor Analysis ## Explain the basic theory of factor analysis and the steps in factor analysis ## Explain the assumptions and requirements of factor analysis ## Specify a factor analysis and interpret the output
KMeans Cluster Analysis ## Explain the basic theory of cluster analysis and the steps in doing a cluster analysis ## Explain the approach of KMeans cluster analysis ## Specify a KMeans cluster analysis and interpret the output
TwoStep Cluster Analysis ## Explain the basic approach of TwoStep cluster analys... [Read More]
IBM SPSS Statistics SyntaxCourse Format: Classroom School/Trainer: Global Knowledge Canada IBM Training Centres Training Center(s)/Venue(s): Halifax, Mississauga, Montreal, Ottawa, Toronto, Winnipeg, Canada VSyntax is the command language that gives instructions to SPSS Statistics on how to modify, manage, and analyze your data. Syntax programs can be used to automate repetitive tasks and perform additional options that are not available in the dialog boxes. You will learn the rules of SPSS syntax, how to generate syntax from the dialog boxes, modify and optimize its use. The approach of the course will be that the dialog boxes and syntax are complementary.
Course Content ## Why Syntax? ## Working with Syntax ## Generating Syntax from the GUI ## The Syntax Editor ## Managing Syntax (e.g., log syntax in the Viewer and/or a journal file, Insert syntax from file)
## Syntax for Reading and Saving Data (e.g. for reading and saving SPSS Statistics data files, ExcelTM files, text files) ## Syntax for Defining Variables (e.g. variable and value labels, missing values) ## Syntax for Selecting Cases (e.g. filtering cases, copying selected to new dataset) ## Syntax for Transformations (e.g. Compute, Visual Binning, Recode)
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