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Introduction to SPS S

Dive into an introductory session on SPSS for PSYC 301, covering course structure, data entry, types of SPSS files, and basic SPSS structure. Learn about coding missing data, labels, values, and practice dataset manipulation.

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Introduction to SPS S

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  1. Introduction to SPSS PSYC 301 SPRING 2014 LAB SESSION

  2. Overview of the semester • Course structure • Introduction to SPSS • Data Entry • Preparing Data File Topics we will cover today

  3. Office hour & By appointment (not at the last min. ) • Attendance Issue • Bonus for participation to experiments Overview

  4. Go to START • Search for SPSS • If you want to open a specific file just click over the file. How to open SPSS

  5. Data File (.sav) • Output File (.spv) • Syntax File (which you will not use for this course) Types of SPSS Files

  6. There are two different windows in SPSS • 1st – Data Editor Window - shows data in two forms • Data view • Variable view Basic structure of SPSS

  7. There are two different windows in SPSS • 1st – Data Editor Window - shows data in two forms • Data view • Variable view • 2nd – Output viewer Window – shows results of data analysis • You must save the data editor window and output viewer window separately. Make sure to save both if you want to save your changes in data or analysis. Basic structure of SPSS

  8. Data view • Rows are cases • Columns are variables • The place to enter data • Variable view • Columns define the variable characteristics • Rows define the variables • Name, Type, Width, Decimals, Label, Missing, etc. • Scale – age, weight, income • Nominal – categories that cannot be ranked (ID number) • Ordinal – categories that can be ranked (level of satisfaction) Data view vs. Variable view

  9. Coding Missing Data • There are two types of missing values in SPSS: system-missing and user-defined. • System-missing data is assigned by if you do not define it by on variable view

  10. User-defined missing data are values that the researcher can tell SPSS to recognize as missing. For example, 99 is a common user-defined missing value. To define a variable’s user-defined missing value… Coding Missing Data • Look at your variables in VARIABLE VIEW • Find the column labeled MISSING • Find the variable that you would like to work with. • Select that variable’s missing cell by clicking on the gray box in the right corner. • click DISCRETE MISSING VALUES • enter 9 (99, 999, or 9999 )to define this variable’s missing value

  11. Labels help you to clarify the variables: more detailed description • Values are used to code the categorical variables • Tell you which groups they are in • Determine the numbers corresponding to each category 1  female 2  male 1  low depression 2  medium depressioı 3  high depression Values & Labels

  12. When you have missing data in your data set, you can fill in the missing data with surrounding information so it does not affect your analysis. Coding Missing Data cont. • click TRANSFORM • click REPLACE MISSING VALUES • select the variable with missing values and move it to the right using the arrow • SPSS will rename and create a new variable with your filled in data. • click METHOD to select what type of method you would like SPSS to use when replacing missing values. • click OK and view your new data in data view

  13. Practice on DataSet1 Practice

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