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Research process
Formulation of the research topic
Overview of the literature
Objectives and hypotheses
Development of the research plan and methodology
Data collection, data processing, and statistical analysis
Interpretation of results and comparison with data from the literature
Evaluation of hypotheses
Conclusions
Hypothesis
A statement or assumption concerning one or more populations. The validity of a hypothesis is tested based on data derived from a sample (or samples).
Qualitative-Categorical
Nominal scale - Eye color, gender, marital status
Ordinal scale - Exam scores, ranking, cancer stage
Quantitative-Numeric
Interval scale - Number of injuries, temperature
Ratio scale - Body weight, age, range of motion
Nominal scale
symbols and numbers used solely for identification (gender, place of residence); they do not possess any of the characteristics of real numbers and cannot be ranked.
Ordinal scale:
numbers and symbols suitable for establishing an order among the objects under study. Differences in the values of the variable are not interpretable (grades, educational attainment, product ratings).
Interval scale:
examines measurable data, has a defined unit of measurement, so differences are meaningful (age, date of birth, intelligence); an absolute zero point is not meaningful.
Ratio scale:
a numerical value that expresses the characteristics of objects. It can be ordered, and the differences in their ratios are meaningful (body weight, height), and it includes an absolute zero point.
Continuous variables
Measures of central tendency
Measures of dispersion
Measures of central tendency
mean median mode
Measures of dispersion
standard deviation
IQR
Range
Categorical variables
Count (frequency) n (%)
Parametric tests
• Greater reliability
• More rigorous testing
• They have strict usability requirements
use bar charts
Non-Parametric tests
• Weaker tests
• No strict usability criteria
• If parametric tests are not applicable, then use them
use box plot