1. data analysis processing data editing data process for coding 2
Post on 31-Dec-2015
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EDITING DATA Data Cleaning
Checking the completed instruments; to identify and minimize
errors incompleteness inconsistencies misclassification etc. (illegible writing)
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CODING DATA
2 Considerations for Coding:Measurement of a variable (scale?,
structure – open/closed ended?).
Communication of findings about a variable (measurement scale?, type of statisitical procedures?) (e.g., Ratio scale – mean, mode, median)
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PROCESS FOR CODING: For analysis using computer, data must
be coded in numerical values. The coding of raw data involves 4 steps:
Developing a code book (master-code book)Pre-testing the bookCoding the data; and Verifying the coded data.
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DEVELOPING A FRAME OF ANALYSIS Develop from beginning of research
and evolve continuously to end.
Frame of analysis: Identify variable to analyseDetermine method to analyseDetermine cross-tabulations needed Determine which variable to combine for
constructing major concepts or develop indices
Identify which variable for which statistical procedures
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UNIVARIATE ANALYSIS Is the examination of the distribution
of cases on only one variable at a time.
Distributions Central tendency Dispersion
Can be generated thro’ Descriptive statistics in the SPSS.
Purpose of univariate analysis is purely descriptive.
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The full original data usually difficult to interpret.
Data reduction is the process of summarizing the original data to make them more manageable; while maintaning the original data as much as possible.
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DISTRIBUTIONS Attribute of each each case under study
in terms of the variable in question. Reporting marginals E.g., how many respondents, what % of
them fall under a certain variable.500 of 1000 FEM students have
CGPA = 3.5 & above.50% of 1000 FEM students.
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FREQUENCY DISTRIBUTION
Shows the number of cases having each of the attributes of a given variable.
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CENTRAL TENDENCY
Reporting summary In term of averages
Mode (most frequent attribute)Mean (arithmetic mean)Median (middle attribute)
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WHICH MEASURE OF CENTRAL TENDENCY TO USE?
Measure Level of Measurement
Examples
Mode Nominal Eye color, party affiliation
Median Ordinal Rank in class, birth order
Mean Interval & ratio Speed of response, age in years
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DISPERSION
Spread of raw data/info of a variable. Detailed information of distribution of a
variable.Range (simplest measure)PercentileStandard deviation (more sophisticated)
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Range: distance separating the highest from the lowest value.
(e.g., the respondents mean age is 22.75 with a range from 20 to 26).
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PERCENTILE A number or score indicating rank by
telling what percentage of those being measured fell below that particular score.
e.g., scored 75th percentile, means 75% of the other people scored below your score and 25% scored at or above your score.
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STANDARD DEVIATION
Is a measure of the average amount the scores in a distribution deviate from average (mean) of the distribution.
Observation near mean, small SD. Observation far from mean, large SD.
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BIVARIATE ANALYSIS Focuses on the relationships/association
between two variables.
Among the many measures of bivariate association are eta, gamma, lambda, Pearson’s r, Kendall’s tau, and Spearman’s rho.
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