How to Enter Data in SPSS 29 Version: A Step-by-Step Guide for Beginners

In this video, you will learn how to enter data in SPSS, a statistical software package widely used in social sciences and other fields. You will see how to enter different types of data, such as likert scale data and semantic differential scale data, and what are the cautions to avoid errors and ensure validity.

Likert scale data are interval-level data that measure the level of agreement or disagreement with a statement, using a series of answer options ranging from strongly agree to strongly disagree. Semantic differential scale data are also ordinal data that measure the attitude or perception of an object using a series of bipolar adjectives with opposite meanings, such as good-bad, fast-slow, etc.

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To enter Likert scale data in SPSS, you need to define your variables in the variable view, assign numeric values to each answer option, and enter the data in the data view. To enter semantic differential scale data in SPSS, you need to follow the same steps but also specify the labels for each pair of adjectives.

Some of the cautions to enter data in SPSS are:

Make sure the data type and format match the type of data you are entering. For example, use string variables for text data and numeric variables for numbers.
Make sure the values and labels are consistent and accurate. For example, do not assign the same value to different answer options or labels, and do not misspell or omit any labels.
Make sure the data are complete and free of missing values. For example, do not leave any cells blank or use invalid values. If you have missing values, you need to handle them appropriately, such as using a special code or excluding them from analysis.
Make sure the data are reliable and valid. For example, do not enter data that are biased, inaccurate, or irrelevant. If you have outliers or extreme values, you need to check them for errors or explain them.
By following these steps and cautions, you will be able to enter data in SPSS correctly and efficiently. You will also be able to perform various statistical analyses on your data and interpret the results. I hope you find this video helpful and informative. Thank you for watching.