IBM: Introduction to Statistical Analysis Using IBM SPSS Statistics SPVC

Introduction to statistical analysis

• Explain the basic steps in the research process.
• Explain the differences between populations and samples.
• Explain the differences between experimental and non-experimental research designs.
• Explain the differences between independent and dependent variables.

Data distributions for scale variables

• Use options in Frequencies, Descriptives and export procedures.
• Interpret results from Frequencies, Descriptives and export procedures.

Data distributions for categorical variables

• Use options in the Frequencies procedure.
• Interpret results from the Frequencies procedure.

Understanding theoretical concepts and data distributions

• Describe the measurement levels used in IBM SPSS Statistics.
• Use measures of central tendency and dispersion.
• Use normal distributions and z-scores.

Relationships between categorical variables

• Use options in the Crosstabs procedure.
• Request appropriate statistics for a crosstab.
• Interpret cell counts and percentages in a crosstab.
• Use the chi-square test, interpret its results and check its assumptions.
• Use Chart Builder to visualise a crosstab.
• Use additional syntax-only crosstab features.

Making inferences about populations from samples

• Explain the influence of sample size.
• Explain the nature of probability.
• Explain hypothesis testing.
• Explain the different types of statistical errors and power.
• Explain the differences between statistical and practical significance.

Paired-samples t-test

• Use the paired-samples t-test procedure.
• Interpret paired-samples t-test results.

Independent-samples t-test

• Check the assumptions of the independent-samples t-test.
• Use the independent-samples t-test to test differences in means.
• Interpret independent-samples t-test results.
• Use Chart Builder to create an error bar chart showing mean differences.

One-way analysis of variance

• Use options in the analysis of variance procedure.
• Check analysis of variance assumptions.
• Interpret analysis of variance results.
• Use Chart Builder to create an error bar chart of mean differences.

Regression analysis

• Explain linear regression and its assumptions.
• Explain options in the Linear Regression procedure.
• Interpret Linear Regression procedure results.
• Use automatic linear modelling to perform regression.

Bivariate correlations and plots for scale variables

• Assess the relationship between two scale variables using scatterplots.
• Explain Pearson's correlation coefficient and its assumptions.
• Interpret a Pearson correlation coefficient.
• Explain options in the Bivariate Correlations procedure.

Non-parametric tests

• Describe when non-parametric tests can and should be used.
• Describe options in the non-parametric tests procedure dialog box and tabs.
• Interpret the results of several types of non-parametric tests.