Standard Deviation
The context typically varies by SD from the mean of mean.
Percentile
Percentile % of context are less than or equal to value.
z-score
Specific value with context is z-score standard deviations above/below the mean.
When describing a distribution, use
GSOCS: Gaps, shape, outliers, center, spread.
Correlation (r)
The linear association between x-context and y-context is weak/moderate/strong (strength) and positive/negative (direction).
Residual
The actual y-context was residual above/below the predicted value when x-context = value.
Y-intercept
The predicted y-context when x = 0 context is the y-intercept.
Slope
The predicted y-context increases/decreases by slope for each additional x-context.
Standard Deviation of Residuals (s)
The actual y-context is typically about s away from the value predicted by the LSRL.
Coefficient of Determination (rĀ²)
About rĀ²% of the variation in y-context can be explained by the linear relationship with x-context.
When describing the relationship, use
DUFS: Direction, unusual features, form, strength.
Probability P(A)
After many many context, the proportion of times that context A will occur is about P(A).
Conditional Probability P(A|B)
Given context B, there is a P(A|B) probability of context A.
Expected Value (mean, mew)
If the random process of context is repeated for a very large number of times, the average number of x-context we can expect is expected value.
Binomial Mean (mew subscript x)
After many, many trials the average # of success context out of n is sample mean.
Binomial Standard Deviation (sigma subscript x)
The number of success context out of n typically varies by sample std from the mean of sample mean.
Standard Deviation of Sample Proportions
The sample proportion of success context typically varies by proportion std from the true proportion of p.
Standard Deviation of Sample Means
The sample mean amount of x-context typically varies by mean std from the true mean of mean of x.
Confidence Interval
We are % confidence that the interval (A, B) captures P, the true parameter context.
Confidence Level
If we take many, many samples of the same size and calculate a confidence interval for each, about confidence level % of them will capture the true parameter in context.
p-value
Assuming Ho in context is true, there is a p-value probability of getting the observed result or less/greater/more extreme purely by chance.
Conclusion for a Significance Test
With a p-value of p-value, less than/greater than alpha, we reject/fail to reject Ho. We do/do not have convincing evidence that Ha in context.
Type 1 Error
The Ho context is true, but we find convincing evidence for Ha context.T
Type 2 Error
The Ha context is true, but we donāt find convincing evidence for Ha context.
Power
If Ha context is true at a specific value there is power probability the significant test will correctly reject Ho.
Standard Error of the Slope
The slope of the sample LSRL for x-context and y-context typically varies from the slope of the population LSRL by about SE of slope.