Upload
derrick-hamilton
View
222
Download
0
Embed Size (px)
Citation preview
Quantifying Data
Data EntryDefine variables, enter case data, conduct runs
Coding and Recoding
– If numeric values not pre-assigned, decide on coding system
– If there is open-ended data, would need to decide how to deal with responses
Defining your variables
Data CleaningReread each set of responses back (immediately)
to confirm accuracy
“Possible-code cleaning”– easiest way to check is to run a frequency
distribution
Contingency cleaning– On the “if” questions
“Sort” by response – do you recycle… then check the “what do you
recycle” variable
Can also run cross tabs and make sure cells are empty
Basic Analysis – Measures of Central TendencyBasic Analysis – Measures of Central Tendency Mean: sum of values divided by the
number of cases– simple average
Median: middle attribute in a list of observed attributes – extreme cases eliminated
Mode: most frequently occurring attribute– used with nominal variables, i.e.. sex
• most respondents were women• usually report with percentage, 60% were
women
Cross Tabs
Used often with Bivariate data
Convention usually places
– “independent variables” across top in columns
– “dependent variables” in rows below
Coding and data entry options
Transfer sheetsTransfer sheets are special forms ruled off in 80 columns
Edge codingEdge coding involves recording code #'s in margins of questionnaires
Direct data entryDirect data entry involves entering data directly into computer; eliminating transfer sheets
Data entry by interviewerData entry by interviewer (CATI)
Optical scan sheetsOptical scan sheets
Coding
What is it? – It is the assignment of numerical values to
information or responses gathered by a research instrument
Codebook: describes the locations of variables and lists the codes assigned to the attributes of the variables
Data Management Process
concerned with the process by which raw data gathered by some instrument are converted into numbers for analysis purposes
Collect information with data gathering instrument
Use codebook to transfer this information to a transfer sheet or code sheet (optional)
Create data file from information on code sheet by entering data from a computer keyboard
Check/clean up data file for accuracy – Data cleaning done by– Computer edit programs – Examine distributions – Contingency cleaning
What about open-ended items?
– Read through responses a create a preliminary code based on responses
– If more than 10% of responses fall into "other" category, code needs to be revised to include many of these responses
Elementary Quantitative Analyses
To understand the meaning of univariate, bivariate, and multivariate analysis
To become familiar with the meaning of several univariate and bivariate statistics
Analysis Strategies
Why do we have to have them?
– People who read our ‘research’ are interested in the highlights
– Should try to communicate findings in an understandable and ‘painless fashion’
Three types of analysisUnivariate analysis
– the examination of the distribution of cases on only one variable at a time (e.g., college graduation)
Bivariate analysis – the examination of two variables
simultaneously (e.g., the relation between gender and college graduation)
Multivariate analysis – the examination of more than two variables
simultaneously (e.g., the relationship between gender, race, and college graduation)
“Purpose”
Univariate analysis
– Purpose: description
Bivariate analysis
– Purpose: determining the empirical relationship between the two variables
Multivariate analysis
– Purpose: determining the empirical relationship among the variables
Types of StatisticsTechniques that summarize and describe
characteristics of a group or make comparisons of characteristics between groups are knows as descriptive statistics.
Inferential statistics are used to make generalizations or inferences about a population based on findings from a sample.
The choice of a type of analysis is based on the evaluation questions, the type of data collected, and the audience who will receive the results.
Univariate AnalysisInvolves examination of the distribution
of cases on only ONE variable at a time
Frequency distributionsFrequency distributions are listings of the number of cases in each attribute of a variable– Ungrouped frequency distribution– Grouped frequency distribution
ProportionsProportions express number of cases of the criterion variable as part of the total population; frequency of criterion variable divided by N
Percentages Percentages are simple 100 X proportion – Or [100 X (frequency of criterion
variable divided by N)]
RatesRates make comparisons more meaningful by controlling for population differences
Measures of Central Tendency
Measures of central tendencyMeasures of central tendency reflect the central tendencies of a distribution
– ModeMode reflects the attribute with the greatest frequency
– Median Median reflects the attribute that cuts the distribution in half
– MeanMean reflects the average; sum of attributes divided by # of cases
Measures of Dispersion
Measures of dispersionMeasures of dispersion reflect the spread or distribution of the distribution
– RangeRange is the difference between largest & smallest scores; high – low
– VarianceVariance is the average of the squared differences between each observation and the mean
– Standard deviationStandard deviation is the square root of variance
Types of Variables
Continuous:Continuous: increase steadily in tiny fractions
Discrete:Discrete: jumps from category to category
Subgroup Comparisons
Somewhere between univariate & bivariate, are Subgroup Comparisons
Present descriptive univariate data for each of several subgroups– Ratios: compare the number of
cases in one category with the number in another
Bivariate Analysis
Bivariate analysisBivariate analysis focus on the relationship between two variables
Contingency TablesFormat: attributes of independent
variable are used as column headings and attributes of the dependent variable are used as row headings
Guidelines for presenting & interpreting contingency tables – Contents of table described in title – Attributes of each variable clearly described – Base on which percentages are computed
should be shown – Norm is to percentage down & compare across– Table should indicate # of cases omitted from
analysis
Multivariate Analysis
Multivariate AnalysisMultivariate Analysis allow the separate and combined effects of the independent variable to be examined