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Week 3B: intro to inferential statistics (statistical models (represents…
Week 3B: intro to inferential statistics
inferential statistics
estimate what happens in a population based on data from a sample
estimate= not confident
makes decisions based on data
draw inferences about data collected
population
The collection of units (e.g., people) to which we want to generalize a set of
findings or a statistical model
sample
A smaller (but hopefully representative) collection of units from a population
used to determine truths about that population
statistical models
represents what is happening in the real world
mean is hypothetical value--> mean is statistical model
model fit to our data
smaller error= the better the model fits the data
hypothetical value: model created to summarize data
deviance= error (rearrange formula)
SD informs us of the fit to the data
ASSESSING HOW CLOSELY THE MODEL FITS REAL LIFE THROUGH ERROR--> the smaller the errors the better the fit
making infrences
distribution
frequency
empirically observed
histogram
real values you measured
probability
what you think is going on in the real world
expected values
z-score
empirical rule
knowing something about the probability between the distributions
sampling distribution
μ = population mean
x(bar)= sample mean
having a mean for a population then taking samples and comparing the mean of the sample to the mean of the population
create normal b distribution based on all sample means
central limit theorum
sample distribution will always be normal/approach normality
as samples get large (greater than 30), the sampling distribution has a normaL distribution with a mean equal to the population mean
t-distribution
when less than 30 samples are collected and distribution is not normal
t-values
standard error
standard deviation of sample means
how representative a sample is of a population
confidence intervals
confidence intervals
hypothesis
significance
how unlikely an event happened by chance
Null Hypothesis Significance Testing (NHST)- p-value
p < .05 = significant
p > .05 = not significant
affected by sample size
Statistically significant does not mean substantially significant
significant= sample mean differs from hypothetical value