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Unit 8: Sampling Distribution - Coggle Diagram
Unit 8: Sampling Distribution
Differentiate between
descriptive
and
inferential statistics
Descriptive statistics
-Collecting, presenting, and describing data either for population or simple information.
Inferential statistics
-Drawing conclusions and/or making decisions concerning a population based only on sample data.
Concept of a
sampling distribution
Defined as the process of selecting some observations (subjects) from all the observations (subjects) from a particular group or population.
Properties:
The mean of the sampling distribution will equal the mean of the population
Sampling distribution of X is approximately normal distributed if:
the population is
normally distributed
, or
sample size > or equal to 30 through CLT through the shape of population is
not normal
Central Limit Theorem
and its importance
As the sample size gets large enough
The sampling distribution becomes almost normal regardless of shape of population
Mean and standard deviation
for the
sampling distribution of the sample mean
Z-value for the sampling distribution of X
x= sample mean
u= population mean
o= standard error of the mean
Sampling Distribution of Sample Mean
Why Sample?
High precision
Less costly
Less time consuming
Sampling theory is a study of the relationship that exist between a
population
and
samples
drawn from the population.
Sampling theory
Used in determining whether observed differences between two samples are actually due to chance variation or whether they are significant
provide a
logical basis
for
using samples to make inferences about populations
