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0G514G – Introduction to Statistical Analysis Using IBM SPSS Statistics

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Introduction to Statistical Analysis Using IBM SPSS Statistics (V23) 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, the assumptions made by each method, 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 underlying 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 Length: 2 day(s)

Course Price: $1400 CAD

Available Course Formats:

  • In-class
  • Instructor Led Online
  • Self-Paced Virtual Classroom

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Course: 0G514G – Introduction to Statistical Analysis Using IBM SPSS Statistics

Introduction to Statistical Analysis

  • Explain the difference between a sample and a population
  • Explain the difference between an experimental research design and a non-experimental 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 Hypotheses-Theory

  • 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 One-Sample T Test to test a hypothesis about a population mean
  • Use the Paired-Samples T Test to test on an ""before-after treatment"" effect
  • Use the Binomial Test to test a hypothesis about a population proportion

Test the Relationship between Categorical Variables

  • Use the Chart Builder to visualize the relationship between two categorical variables
  • Use percentages in Crosstabs to describe the relationship between two categorical variables
  • Use the Chi-Square test in Crosstabs to test the relationship between two categorical variables

Test the Difference between the Means of Two Groups

  • Use the Chart Builder to create an error bar and boxplot to visualize the difference between groups
  • Use Explore and Means to describe the differences between groups
  • Use the Independent-Samples T Test to test whether the difference between two group means is statistically significant

Test the Differences between More than Two Group Means

  • Use One-Way ANOVA to determine whether there are statistically significant differences between means of three or more groups
  • Use post hoc tests to identify differences between group means

Test the Relationship between Scale Variables

  • Use the Chart Builder to create a scatterplot to assess the relationship between two scale variables
  • Explain when the correlation can be used
  • Perform a hypothesis test on the correlation

Predict a Scale Variable

  • Use Regression to predict a scale variable with one or more scale variables
  • Use Automatic Linear Modeling to predict a scale variable with categorical and scale variables

Use Nonparametric Tests

  • Describe when Nonparametric Tests should and can be used
  • Use Nonparametric Tests for two or more independent samples
  • Use Nonparametric Tests for two dependent samples

Audience

This intermediate course is intended for:

  • 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 with limited or no statistical background
  • Anyone who wants to refresh their knowledge and statistical experience that were gained many years ago

Prerequisites

You should have:

  • General computer literacy
  • Completion of the "Introduction to IBM SPSS Statistics" and/or Data Management and Manipulation with IBM SPSS Statistics" courses or experience with IBM SPSS Statistics (Version 15 or later) including familiarity with opening, defining, and saving data files and manipulating and saving output

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.

On-Demand

This course is available on-demand: request a specific course, location, time frame and/or format by completing this form. This offering increases schedule flexibility and allows us to accommodate people with different availabilities.

Customized Courses

On-site courses can also be customized based on user roles and needs within your organization. This option allows lower costs in travel and time and increased flexibility in scheduling. This format also enables students to work with the organization's data - adding value to the learning experience. This makes the training relevant and applicable to the students; daily tasks and therefore, results in a quicker path to productivity.