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Inferential statistics, Hypothesis testing - Coggle Diagram
Inferential statistics
Draw conclusions from samples and generalize it to population
Principles
Estimation
Point estimate
from sample
e.g. Mean, median
Interval estimate
Additional information
standard deviation
& sample size
Confidence interval
Measure of researcher's uncertainty
Errors
Systematic error
Bias
Non-systematic error
Error variance
Type of error
Type 1 error :-1::skin-tone-5:
alpha error
researcher controls
alpha < 0.05 : reject the null hypothesis
Rejecting the Null hypothesis
which is true :red_cross:
Type 2 error
Accepting the null hypothesis
:check: which is false
Beta error
Ingredients
size of the observed difference / relationship
variability in the sample
sample size
Power
Correctly rejecting the null hypothesis
fulfill the aim
Hypothesis testing
2 hypothesis
.
Significance
level
Statistical strength of a statistical test
Probability
Type 1 error
Wrongly rejecting the null hypothesis as false
Null
hypothesis
NO relationships
Means are same | difference between the means are zero
Alternate
hypothesis
Null hypothesis is false
systematic way of testing the idea or claim about a population
Variability
chance
True difference
Sampling error