Population vs. Sample
Population is the entire group you want to draw conclusions about. A Sample is the specific group that you will collect data from.
Parameter vs. Statistic
A Parameter describes an entire population (like population mean μ). A Statistic describes a sample (like sample mean X̄).
Point Estimator
A sample statistic used to estimate a population parameter. For example, the sample mean is a point estimator of the population mean.
Confidence Interval
An interval of numbers within which we expect a population parameter to fall, with a specified level of certainty (e.g., 95%).
Margin of Error
The range of values below and above the sample statistic in a confidence interval. It reflects the uncertainty of our estimate.
Null Hypothesis (H0)
The default assumption or 'status quo' that there is no relationship, no difference, or no effect. We assume H0 is true until proven otherwise.
Alternative Hypothesis (H1)
The claim you are trying to prove or the statement that there is an effect or a difference.
P-value
The probability of getting your observed sample data, or something more extreme, assuming the Null Hypothesis is actually true.
Significance Level (α)
The threshold we set for deciding whether a P-value is low enough to reject the Null Hypothesis (commonly set at 0.05).
Type I & Type II Errors
Type I: Rejecting H0 when it's actually true (False Positive). Type II: Failing to reject H0 when it's actually false (False Negative).