L-I-N-E-R
Paired T Test
Two-sample T Test
Refer to Khan academy: Example of hypotheses for paired and two-sample t tests
Conditional Probability
It’s NOT just both events happened, it’s asking the probability of one event AFTERanother event happened.It’s based on a happened event, that’s why you’re to divide the probability of the happened event.
Notation
Sampling Distribution
It’s just taking out the parameters(Mean/SD..) from different samples of the SAME population, and make them as a distribution. etc., _Distribution of means_, _Distribution of standard deviations_…
p-value
p-value stands for “probability value”, which is the most confusing concept in Hypothesis testing. So it’s necessary to pick it out here before exceeding to the Significance Testing.
Refer to youtube: Hypothesis Testing 5: p values (one sample t test)
Confidence Interval
Since there will always be sampling error for estimating the true population, so it’s a good practice to have a confidence interval while doing estimation on samples.
Refer to youtube: Understanding Confidence Intervals: Statistics HelpRefer to article…
Mean Absolute Deviation
The Mean absolute deviation is the absolute average of all deviations.
Mean absolute deviation
The deviation is the distance from the value to the mean value. It's used to describe how the values looks like or how they're laid on the axis, are they close to each other or…
The deviation
mean
Bernoulli Distribution
It is the discrete probability distribution of a random variable which takes the value 1 with probability p and the value 0 with probability q=1-p, that is, the probability distribution of any single experiment that asks a yes–no question; the question results in a boolean-valued…
discrete probability distribution
1
0
q=1-p
yes–no questio
boolean-valued
Testing Errors
Type 𝐈 & Type 𝐈𝐈 Errors
Type I & Type II Errors are conditional…
