Lecture Notes
Field Research Methods
Psyc 311

Lecture 1 | Lecture 2 | Lecture 3 | Lecture 4 | Lecture 5 | Lecture 6 | Lecture 7| Lecture 8 | Lecture 9 |
Lecture 10 | Lecture 11 | Lecture 12 | Lecture 13 | Lecture 14 | Lecture 15 | Lecture 16 | Lecture 17

Lecture Notes:

Field Research Methods (PSYC 311)

LECTURE 11: Survey Data Analysis

Data Entry - Process of taking completed questionnaires\surveys and putting them into a form that can readily be analyzed

Series of options need to consider:

  1. Decide on a file format.

  2. Devise code for analysis

    1. Make coding translation simple (or nonexistent!)

        Minimize effort and risk of coding errors
        Item-level: Leave #s as #s (#s can be nominal).
        Reverse coding/Unfolding complex response formats.
        Test-level: Code questions in order of appearance.
        Be consistent in assigning values with similar responses
        Identify question groups within test.
        Facilitates data interpretation

    2. How missing data are treated

        Non ascertained Information: information not obtained because of interviewer or respondent performance.
        Failure to ask question
        Failure to obtain appropriate response
        Refusal to answer question (separate)

      Inapplicable Information: information does not apply to a particular respondent

      Unknown information: information as to respondent's claim of awareness (How to treat "Don't know" option)

    3. Entry of Data

        Number of translation steps between subject's response and readable data file
        Computer assisted techniques: 1
        Digital answer format (Scantron): 3
        Entry by hand: 4
        Impacts ability to check quality of data entry (accuracy, reliability)

    4. Clean Data File

        Examine each data file to ensure each record is complete and in order
        Remove non-legal codes
        Replace with information from original response format
        Importance of verification

      Data Analysis

        Organization of data to better understand distribution
        Ordered listing of scores
        Record the frequency (i.e., number of respondents) located within each category
        Use original measurement scale

      Frequency Table

        Qualitative Data: relative frequencies

        1. Proportion - frequency within category divided by total number
        2. Percentage - proportion (.01)

        Quantitative Data: cumulative frequencies

        1. Proportion\Percentage
        2. Cumulative Frequency - begin with interval of least magnitude and add each subsequent frequency
        3. Cumulative Percentages - divide cumulative frequency of each interval by total N

      Graphs

        Qualitative Data: Bar Graph

        1. Width of bars constant
        2. Bars separated by constant distance
        3. Height of the bar corresponds to frequency of category

      Quantitative Data: Histogram\Frequency Polygon

      1. Histogram

        1. Similar to Bar Graph
        2. Bar width represents real limits (touch)

      2. Frequency Polygon

        1. Values represented as points
        2. Generally used to express time dimension

        Other Analyses: