3 Flashcards
Does the mean follow the rule of linearity?
Yes
Although variance does follow the rules of linearity, what else do you need to do (except summing variances)?
Adding a square
If we can take multiple samples of a population, what is the better thing to do?
Take one large sample
If you take multiple samples, you can create a histogram of?
Means for each sample.
How can a histogram of means for each sample useful?
You can compare the mean and variance for the histogram of means and compare it to the actual mean and variance of the population.
If you have larger sample sizes, then the means are?
Closer together and less spread out.
Standard error?
Estimate of standard deviation of its sampling distribution. Most useful for a histogram of means for many samples.
Confidence interval?
Provides a plausible range for a parameter (believable or reasonable). All values for the parameter lying within the interval are plausible, given the data, whereas those outside are unlikely.
!!!!!What does it mean to have a 95% confidence interval for the mean?
The means of many samples have a 95% chance of falling within the confidence interval.
Pseudoreplication?
Error that occurs when individuals measurements are not independent, but they are treated as though they are.
Mutually exclusive?
Two events that cannot both be true
How to write mutually exclusive probability?
Pr(A and B) = 0
Probability distribution?
The true relative frequency of all possible values of a random variable.
Addition principle for two mutually exclusive events: Pr[A or B] = ?
Pr[A] + Pr[B]
General addition principle probability of intersecting sets when events are or are not mutually exclusive: Pr[A or B]?
Pr[A] + Pr[B] - Pr[A and B]
Independence?
Two events are independent if the occurrence of one gives no information about whether the second will occur.
Multiplication rule if two events are independent, then: Pr[A and B] = ?
Pr[A]*Pr[B]
!!!!!Mutually exclusive vs independent?
General formula for “at least one” out of n independent trails, where prob in each trial is Pr(A): Pr(at least one A) = ?
1 - (1 - Pr(A))^n
Overall probability of a dependent event?
Dissecting the dependent events into its independent events, and add them up depending on the original problem.
Conditional probability of an event is the probability of that event occurring given that a condition is met is Pr[X|Y]. Pr[X|Y] = ?
Pr[A and B] / P[A]
General multiplication rule whether or not events A and B are independent: Pr[A and B] = ?
Pr[A]Pr[B|A]
Hypothesis testing?
Certain testing approaches to determine whether the probability is valid enough
