Interpretations Flashcards
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
Describe a distribution
Be sure to address shape, center, variability, and outliers in context.
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 = #
y-intercept
the predicted y-context when x=0 context is 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 [r^2]
about r^2% of the variation in y-context can be explained by the linear relationship with x-context
Describe the relationship
be sure to address strength, direction, form and unusual features in context
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, [µ])
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 (decimals are OK)
Binomial Mean [µx]
after many, many trials, the average number of successful context out of n is µx
Binomial Standard Deviation (σx)
the number of success context out of n typically varies by σx from the mean of µx
Standard Deviation of Sample Proportions [σ phat]
the sample proportion of success context typically varies by σ phat from the true proportion of p
Standard Deviation of Sample Means [σ xbar]
the sample mean amount of x-context typically varies by σ xbar from the true mean of µx
Confidence Interval (A, B)
We are C% confident that the interval from A to B captures 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, there is a p-value probability of getting the observed result or less/greater/more extreme, purely by chance
Conclusion for a Significance Test
because p-value p-value < / > ∂, we reject/fail to reject Ho. we **do/do not ** have convincing evidence for Ha in context
Type 1 Error
The Ho context is true, but we find convincing evidence for Ha context
Type II Error
the Ha context is true, but we don’t find convincing evidence for Ha context