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CMNS201 - Lab 2. SPSS Variables and Cases

CMNS201 - Lab 2. SPSS Variables and Cases

Alberto Lusoli

January 25, 2022
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  1. Variables and cases
    SPSS LABORATORY 2

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  2. INDEX
    1. Previous lecture recap
    2. Calendar
    3. What is a Dataset
    4. Variable view

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  3. Photo: Startup Weekend Hackathon. Nov.2014
    LAST WEEK RECAP
    ■ Downloaded, installed and activated SPSS
    ■ Imported Music-1.xlsx dataset
    Still having problems installing SPSS?
    ○ Book an appointment for office hour (Thursday, 12.30 - 1.20)
    ○ Tech problem? Email [email protected]

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  4. Photo: Startup Weekend Hackathon. Nov.2014
    SET UP SPSS
    ■ Launch SPSS.
    ■ Go to Canvas
    ○ Assignments > SPSS Lab 2 - Intro to SPSS
    ○ Download the Music-1 Dataset (in Excel, not PDF)
    ■ Import the dataset on SPSS
    ○ File > Import > Excel
    ○ Click OK in the preview window

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  5. Photo: Startup Weekend Hackathon. Nov.2014
    WHAT IS A DATASET
    Cases
    Variables

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  6. Photo: Startup Weekend Hackathon. Nov.2014
    WHAT IS A DATASET
    Population

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  7. Photo: Startup Weekend Hackathon. Nov.2014
    A SURVEY DATASET
    Student ID Name Age Nationality GPA Height Eyes color
    1324234 Rick 21 CA 3.2 181 Hazel
    223423 Maria 22 US 2.1 160 Green
    354353 Eddie 25 ES 3 176 Blue

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  8. Photo: Startup Weekend Hackathon. Nov.2014
    A SURVEY DATASET
    Student ID Name Age Nationality GPA Height Eyes color
    1324234 Rick 21 CA 3.2 181 Hazel
    223423 Maria 22 US 2.1 160 Green
    354353 Eddie 25 ES 3 176 Blue
    Participants
    Answers
    to survey
    questions

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  9. Photo: Startup Weekend Hackathon. Nov.2014
    THE MUSIC-1 DATASET

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  10. Photo: Startup Weekend Hackathon. Nov.2014
    WHAT IS A DATASET
    Songs
    Songs
    features

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  11. Photo: Startup Weekend Hackathon. Nov.2014

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  12. Photo: Startup Weekend Hackathon. Nov.2014
    THE DATA VIEW WINDOW: VARIABLE VIEW

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  13. Photo: Startup Weekend Hackathon. Nov.2014

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  14. Photo: Startup Weekend Hackathon. Nov.2014
    The variable name can be changed.
    Variable names appear in the heading of the data view.
    Variable names should be clear, concise and cannot contain
    spaces.
    VARIABLE NAME

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  15. Photo: Startup Weekend Hackathon. Nov.2014
    Not all variables are created equal.
    Numeric: Numeric variables as you might expect, have data
    values that are recognized as numbers. Use this variable for
    both integer and decimal number (dot used to indicate
    decimals, not comma).
    String: also called alphanumeric variables, have values that
    are treated as text
    VARIABLE TYPE

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  16. Photo: Startup Weekend Hackathon. Nov.2014
    VARIABLES IN THE MUSIC-1 DATASET
    8

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  17. Photo: Startup Weekend Hackathon. Nov.2014
    You can assign descriptive variable labels up to 256
    characters. Variable labels can contain spaces and reserved
    characters that are not allowed in variable names.
    Do yourself a favor: everytime you create a dataset, make
    sure to describe what each variable is/means using the
    Label field.
    VARIABLES LABEL

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  18. Photo: Startup Weekend Hackathon. Nov.2014
    Scale: A variable can be treated as scale when its values
    represent ordered categories with a meaningful metric, so
    that distance comparisons between values are appropriate.
    Examples of scale variables include age in years, and
    income in thousands of Dollars.
    VARIABLES MEASURE

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  19. Photo: Startup Weekend Hackathon. Nov.2014
    Ordinal: A variable can be treated as ordinal when its
    values represent categories with some intrinsic ranking. For
    example, levels of service satisfaction from highly
    dissatisfied to highly satisfied. Examples of ordinal variables
    include a degree of satisfaction among the consumers,
    school grades (A, B, C, D, E, F), etc.
    VARIABLES MEASURE

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  20. Photo: Startup Weekend Hackathon. Nov.2014
    Nominal: A variable can be treated as nominal when its
    values represent categories with no intrinsic ranking. For
    example the department of the company in which an
    employee works.
    Examples of nominal variables include region, zip code, or
    gender of individual or religious affiliation.
    VARIABLES MEASURE

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  21. Photo: Startup Weekend Hackathon. Nov.2014
    VARIABLES MEASURE: RULE OF THUMB
    Can the values of a variable be
    ranked?
    NO YES
    Do the values of a variable share
    all the same unit of measurement?
    NO YES
    NOMINAL
    ORDINAL SCALE

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  22. Photo: Startup Weekend Hackathon. Nov.2014
    Are the values of a variable independent, meaning that they cannot be ranked?
    If yes, it’s Nominal.
    Example: First name, Nationality, University name.
    Do the values of a variable share all the same unit of measurement, and they can be ordered?
    If yes, it’s a Scale.
    Examples include Height (cm or ft, in), Age (in years), speed (in km/h), weight (in kg, pounds)...
    Can the values of a variable be ordered according to some meaningful principle and values do not share a
    common unit of measurement?
    If yes, it’s ordinal.
    Examples include school grades (A, B, C, D, E, F), experience (beginner, intermediate, expert), etc.
    VARIABLES MEASURE: RULE OF THUMB

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  23. Photo: Startup Weekend Hackathon. Nov.2014
    ASSIGNMENT 2
    8
    Import the Dataset Music-1.xlsx into SPSS
    1. Go to Variable View
    2. Rename the Variable “Title” to “Song_title”
    3. Write a label that describes the meaning of the variable Tempo (the variable Tempo represents the
    speed of the song in BPM, Beats Per Minute)
    4. Change the Measure of the variables Popularity and Release_date from Scale to Ordinal
    Take a screenshot of Variable View and upload it on Canvas.

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  24. Photo: Startup Weekend Hackathon. Nov.2014
    8

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  25. Photo: Startup Weekend Hackathon. Nov.2014
    TO CONCLUDE…
    8
    1. Save your project.
    2. SPSS project files have the .sav extension. Your saved project includes the data (which means, no
    need to re-import the dataset next time)

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  26. THANK YOU
    Alberto Lusoli
    [email protected]
    Office hour: Thursday, 12.30pm - 1.20pm (please book an appointment in advance via email).

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