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Research Methods. ANALYSING QUANTITATIVE DATA 2. Research Methods. Data: Reduction, Description, Summarising, Estimation, Hypothesising. Analysing Quantitative Data 1. DATA. Plural of ‘datum’ Measurement Number Differing types, inc. levels of measurement Statistical data.
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Research Methods ANALYSING QUANTITATIVE DATA 2 Research Methods Data: Reduction, Description, Summarising, Estimation, Hypothesising. Analysing Quantitative Data 1
DATA • Plural of ‘datum’ • Measurement • Number • Differing types, inc. levels of measurement • Statistical data
DATA MANIPULATION • Why manipulate? • clarity • explanation • exposition • comparison • Forms of manipulation • display • explicit summary or ‘model’ • deviations
UNDERSTANDING DATA • Units of Analysis • cases • subjects • observations • Variables: qualitative & quantitative • Values
STATISTICAL STUFF • Data Matrix • Sample • Population • Primary & secondary data • Levels of measurement • Raw data (& then cooked) • Coding
LEVELS of MEASUREMENT • Concept & construct • Metric & non-metric • Scales • nominal • ordinal • interval • ratio
DATA PREPARATION • Editing & cleaning • Coding • Transformations
EDITING • In the field • ambiguities • inconsistencies • Back at base • missing data • collection error • don’t know • won’t answer • N/A.
PRODUCING the RESULTS I • Topic of interest • conceptualization • population specification • Concepts • operationalization • Variables • measurement • Raw data matrix
PRODUCING the RESULTS II • Population • sampling • Sample • response • Raw Data Matrix • editing & coding • Final data matrix • analysis • Results
DATA CODING • Numeric Variables • String Variables • Single response • Multiple response • Variable names & labels
DATA ENTRY • Computer based • Advice: look at your data before analysis • Input > Analysis > Output
ANALYSIS OBJECTIVES • Base on research purpose • Think them through • Description • Estimation & confidence -inference • Hypothesis testing - inference
DATA DISPLAY • Visual scanning • of initial data set • of simple summary outputs • Select display methods • tables • charts • diagrams • Use a guide! - and work at it!
DATA DESCRIPTION I • Frequency distributions • absolute • relative • cumulative • quartiles etc.. • grouped • Histograms • Polygons
DATA DESCRIPTION II • Central tendency (1st. moment) • Averages • mode • median • mean • arithmetic • geometric • harmonic
DATA DESCRIPTION III • Range • Variance • Deviations • absolute • standardized • root mean square • Skew (2nd. moment) • Kurtosis (3rd. moment)
TYPES of DISTRIBUTION • Binomial • Hypergeometric • Poisson • Chi-square • t-distribution • F-distribution • Normal (Gaussian)
ESTIMATION • Population • Samples • Point estimation • Interval estimation • Confidence levels • Parameters & statistics • Proportion & other parameters
HYPOTHESES • Formal statements • Extend from samples to defined populations • Relationships between two (or more) variables • Testable • Null, alternate • Non-directional, directional • Based on knowledge,theory or status quo
HYPOTHESIS TESTING • Formulate hypotheses • Specify significance level • Select an appropriate test • Identify distribution &rejection area(s) • Apply the test • Conclude on result of test - accept or reject hypothesis
UNIVARIATE & SINGLE SAMPLE • Test of goodness of fit • Test for location • Test for proportion • Test for variability • Test for randomness
MAKING COMPARISONS • Independence in groups (independent measures) • Related measures (non-independent samples) • Distributions • Proportions • Central location • ANOVA
RELATIONSHIPS • Association • Correlation • Regression • Models
MULTI-VARIATE SITUATIONS I • Multiple regression • Discriminant analysis • Canonical correlation • MANOVA • Factor analysis • Cluster analysis • CHAID
MULTI-VARIATE SITUATIONS II • Path models • Structural equations • ...and even more stuff