0G51AG – IBM Statistical Analysis Using IBM SPSS Statistics

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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, as well as 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 as well as how to apply them with confidence, interpret their output, and graphically display the results.

Course Outline:

Course Outline

1. Introduction to statistical analysis
- Identify the steps in the research process
- Principles of statistical analysis

2. Examine individual variables
- Identify measurement levels
- Chart individual variables
- Summarize individual variables
- Examine the normal distribution
- Examine standardized scores

3. Test hypotheses about individual variables
- Identify population parameters and sample statistics
- Examine the distribution of the sample mean
- Determine the sample size
- Test a hypothesis on the population mean
- Construct a confidence interval for the population mean
- Tests on a single variable: One-Sample T Test, Paired-Samples T Test, and Binomial Test

4. Test the relationship between categorical variables
- Chart the relationship between two categorical variables
- Describe the relationship: Compare percentages in Crosstabs
- Test the relationship: The Chi-Square test in Crosstabs
- Assumptions of the Chi-Square test
- Pairwise compare column proportions
- Measure the strength of the association

5. Test on the difference between two group means
- Compare the Independent-Samples T Test to the Paired-Samples T Test
- Chart the relationship between the group variable and scale variable
- Describe the relationship: Compare group means
- Test on the difference between two group means: Independent-Samples T Test
- Assumptions of the Independent-Samples T Test

6. Test on differences between more than two group means
- Describe the relationship: Compare group means
- Test the hypothesis of equal group means: One-Way ANOVA
- Assumptions of One-Way ANOVA
- Identify differences between group means: Post-hoc tests

7. Test the relationship between scale variables
- Chart the relationship between two scale variables
- Describe the relationship: Correlation
- Test on the correlation
- Assumptions for testing on the correlation
- Treatment of missing values

8. Predict a scale variable: Regression
- What is linear regression-
- Explain unstandardized and standardized coefficients
- Assess the fit of the model: R Square
- Examine residuals
- Include 0-1 independent variables
- Include categorical independent variables

9. Introduction to Bayesian statistics
- Bayesian statistics versus classical test theory
- Explain the Bayesian approach
- Evaluate a null hypothesis: Bayes Factor
- Bayesian procedures in IBM SPSS Statistics

10. Overview of multivariate procedures
- Overview of supervised models
- Overview of models to create natural groupings

Course Audience & Prerequisites:

Audience

- Anyone who has worked with IBM SPSS Statistics and wants to become better versed in the basic statistical capabilities of IBM SPSS Statistics Base.
- Anyone who wants to refresh their knowledge and statistical experience.

Prerequisites

• Familiarity with basic concepts in statistics, such as measurement levels, mean, and standard deviation.
• Familiarity with the windows in IBM SPSS Statistics either by experience with IBM SPSS Statistics (version 18 or later) or completion of the IBM SPSS Statistics Essentials (V25) course.

Course Offerings:

Instructor Led In Classroom

Newcomp can directly deliver  IBM Business Analytics courses for Business Intelligence, Performance Management, and IBM Advanced Analytics through the use of in-class training facilities.

Currently,  in-class courses are offered in Markham, Ottawa, Vancouver, Halifax, and Edmonton. Please note that classes can be added to new areas based on demand.

Instructor Led Online

Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples

ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.

Self Paced

Students can receive the same high-quality training, with the same courseware at their own speed and schedule with SPVC.  Individuals with busy schedules can complete a course over a 30-day timeframe at a lower price than in-class or ILO courses. Please note that there is no live interaction with an instructor in this format.

• Course Outline
• Course Audience & Prerequisites
• Course Offerings
• Related Courses

Course Outline

1. Introduction to statistical analysis
- Identify the steps in the research process
- Principles of statistical analysis

2. Examine individual variables
- Identify measurement levels
- Chart individual variables
- Summarize individual variables
- Examine the normal distribution
- Examine standardized scores

3. Test hypotheses about individual variables
- Identify population parameters and sample statistics
- Examine the distribution of the sample mean
- Determine the sample size
- Test a hypothesis on the population mean
- Construct a confidence interval for the population mean
- Tests on a single variable: One-Sample T Test, Paired-Samples T Test, and Binomial Test

4. Test the relationship between categorical variables
- Chart the relationship between two categorical variables
- Describe the relationship: Compare percentages in Crosstabs
- Test the relationship: The Chi-Square test in Crosstabs
- Assumptions of the Chi-Square test
- Pairwise compare column proportions
- Measure the strength of the association

5. Test on the difference between two group means
- Compare the Independent-Samples T Test to the Paired-Samples T Test
- Chart the relationship between the group variable and scale variable
- Describe the relationship: Compare group means
- Test on the difference between two group means: Independent-Samples T Test
- Assumptions of the Independent-Samples T Test

6. Test on differences between more than two group means
- Describe the relationship: Compare group means
- Test the hypothesis of equal group means: One-Way ANOVA
- Assumptions of One-Way ANOVA
- Identify differences between group means: Post-hoc tests

7. Test the relationship between scale variables
- Chart the relationship between two scale variables
- Describe the relationship: Correlation
- Test on the correlation
- Assumptions for testing on the correlation
- Treatment of missing values

8. Predict a scale variable: Regression
- What is linear regression-
- Explain unstandardized and standardized coefficients
- Assess the fit of the model: R Square
- Examine residuals
- Include 0-1 independent variables
- Include categorical independent variables

9. Introduction to Bayesian statistics
- Bayesian statistics versus classical test theory
- Explain the Bayesian approach
- Evaluate a null hypothesis: Bayes Factor
- Bayesian procedures in IBM SPSS Statistics

10. Overview of multivariate procedures
- Overview of supervised models
- Overview of models to create natural groupings

Audience

- Anyone who has worked with IBM SPSS Statistics and wants to become better versed in the basic statistical capabilities of IBM SPSS Statistics Base.
- Anyone who wants to refresh their knowledge and statistical experience.

Prerequisites

• Familiarity with basic concepts in statistics, such as measurement levels, mean, and standard deviation.
• Familiarity with the windows in IBM SPSS Statistics either by experience with IBM SPSS Statistics (version 18 or later) or completion of the IBM SPSS Statistics Essentials (V25) course.

Instructor Led In Classroom

Newcomp can directly deliver  IBM Business Analytics courses for Business Intelligence, Performance Management, and IBM Advanced Analytics through the use of in-class training facilities.

Currently,  in-class courses are offered in Markham, Ottawa, Vancouver, Halifax, and Edmonton. Please note that classes can be added to new areas based on demand.

Instructor Led Online

Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples

ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.

Self Paced

Students can receive the same high-quality training, with the same courseware at their own speed and schedule with SPVC.  Individuals with busy schedules can complete a course over a 30-day timeframe at a lower price than in-class or ILO courses. Please note that there is no live interaction with an instructor in this format.

0G53AG – IBM SPSS Statistics Essentials

This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis process. Students will learn the basics of reading data, data definition, data modification, and data analysis and presentation of analytical results. Students will also see how easy it is to get data into IBM SPSS Statistics so that they can focus on analyzing the information. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base features.