SCMA*2040 Lecture Notes - Lecture 4: Stratified Sampling
Week 4: Sampling
Population: Individual things that make up your data source
Sample: Group of things
Sampling: The act of grouping things
-Homogeneity: Similarity within population;Confuses data when generality is
required > error in judgment
-Heterogeneity: Degree of diversity within population
Deductive Method
-Theory > Testing
-Premise + Premise = Conclusion
-What assumptions have you made?
Inductive Method (Probability)
Used for
-Descriptive ex. satisfaction with teaching style
-Heterogeneous distribution of research objective
-Formally representative sample (same proportions within population)
-What are you trying to analyze? Unit of Analysis
-What is the population you choose from within “The Universe”
Random Samplevery sampling element (unit) listed only once ex.library books
Sampling Errors
-Systematic: sample group narrowed by how population identified, where
population is found
-Random: chance variation ex. coin toss
Representative Sampling
-Qualitative - by nature, think about sampling
-Quantitative - random, stats, unframed data collection
Stratified Sampling
-Population > N=100, 100 students
-Stratified > 40 Early Childhood, 35 Social Work, 20 Justice Studies, 5 Other
-Proportional Stratified Sample > 1:5 20:100
-100 students = 40 Early Childhood n=8, 35 Social Work n=7, 20 Justice Studies
find more resources at oneclass.com
find more resources at oneclass.com
