IBM SPSS Statistics: Getting Started

Learn to read data into IBM SPSS statistics, including Excel imports and file open options. Each column becomes a variable and each row a case, with worksheet and range controls.

This demonstration shows how to import an excel data set into IBM SPSS Statistics, manage variable names with no spaces, underscores allowed, max 64 chars, and inspect data and views.

Explore variable properties in IBM SPSS Statistics, including names, types, labels, value labels, missing values, column width, alignment, and level of measurement, to improve data interpretation and analysis.

Learn to add variable properties in SPSS by using variable view, set width and labels for a numeric variable, define value labels and missing values, and save the data.

Explore how to summarize individual variables with the frequencies procedure for categorical and continuous data, check data quality, identify extreme values, and choose appropriate charts.

Demonstrate the frequencies procedure for nominal and ordinal categorical variables in SPSS, selecting department and overall satisfaction, and interpret mode and median limits, with bar charts based on percentages.

Learn to use the frequency procedure to summarize scale level variables in IBM SPSS, showing mean, standard deviation, percentiles, and a histogram with a normal curve.

demonstrates using the frequencies procedure on a scale level variable to obtain mean, median, mode, min, max, and standard deviation, plus a histogram with a normal curve.

Transform data values for single variables using the transform menu and recoat options in IBM SPSS Statistics. Create or modify variables and use the recall procedure with regrouping examples.

Demonstrates the RICO procedure to recode overall satisfaction from five categories into a two-category set top, with 1 for very satisfied, 2 for others, and 9 for missing data.

Transform data by computing new variables from existing ones using mathematical expressions or functions in the compute variable procedure, with optional subsetting and checks for accuracy.

Shows how to compute an overall satisfaction score from six variables in SPSS, using a numeric expression and the mean function, with checks in data editor and key summaries.

Explore how to describe relationships between two categorical variables using the cross procedure and crosstabs, visualized with the chart builder, and interpreted through counts, percentages, p-values, and chi-square tests.

Learn to perform cross tabulations in SPSS, place gender in columns and overall satisfaction in rows, view column percentages, and assess significance with chi-square.

Learn to create graphs using the chart builder, graph, and template chooser in SPSS, selecting variables, exploring galleries, and adjusting chart properties in the output viewer.

Create a clustered bar chart in the chart builder to visualize the relationship between gender and overall satisfaction, displaying percentages and configuring axes and colors for clear comparison.

Explore the IBM SPSS output viewer, navigating the outline and content panes, and learn to hide, show, move, delete, and insert objects, plus copy, paste, and export output.

Explore the output viewer tools in IBM SPSS Statistics, navigate with the left pane, hide logs, and arrange bar charts beside frequency tables for clearer results.

Copy and paste SPSS output—pivot tables, charts, and text—into Word, PowerPoint, or Excel, or export output for broader use.

Copy and paste SPSS output into other apps using copy special; choose formats such as plain text, rich text, image, or metafile, then paste special in Word or Excel.

Export your output to another application by choosing the file type (Word, text, Excel, DML, PDA, or PowerPoint) and selecting visible, all, or chosen objects.

Export IBM SPSS Statistics output to Excel by selecting all visible objects, choosing Excel format, and configuring workbook options; graphs come in as images while tables adapt to the file.