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Statistical Analysis Using IBM SPSS Statistics (V26) SPVC
Contains: PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace.
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 • 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
• IBM SPS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS Statistics Base. • Anyone who wants to refresh their knowledge and statistical experience.
• Experience with IBM SPSS Statistics (version 18 or later), or • Completion of the IBM SPSS Statistics Essentials course
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 distribution • Identify standardized scores Testing hypotheses • Principles of statistical testing • One-sided versus two-sided testing • Type 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 means • Chart 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: 16 Hours
- Delivery Format: Classroom Training, Online Training
- Price: 1,630.00 USD
- Duration: 16 Hours
- Delivery Format: Self-Paced Training
- Price: 875.00 USD
Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
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Self-Paced Training Terms & Conditions
THIS IS A SELF-PACED VIRTUAL CLASS. AFTER YOU REGISTER, YOU HAVE 30 DAYS TO COMPLETE THE COURSE.
This is a Self-Paced virtual class; it is intended for students who do not need the support of a classroom instructor. If you feel you would better benefit from having access to a Subject Matter Expert, please enroll in the Instructor-Led version instead. Minimal technical support is provided to address issues with accessing the platform or problems within the lab environment.
Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Self-Paced Virtual Classes are non-refundable. Once you purchase a Self-Paced Virtual Class, you will be charged the full price.
After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. A confirmation email will contain your online link, your ID and password, and additional instructions for starting the course.
You can start the course at any time within 12 months of enrolling for the course. After you register/start the course, you have 30 days to complete your course. Within this 30 days, the self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.
If the course requires a remote lab system, the lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system.
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