Term
|
Definition
| when its impossible for both outcomes to occur for a given individual |
|
|
Term
|
Definition
|
|
Term
|
Definition
| the act of creating the event |
|
|
Term
|
Definition
| the number of possible outcomes |
|
|
Term
|
Definition
| p(a)=the total number of observations favoring event a/ the total number of observations |
|
|
Term
|
Definition
| likelihood of an event given some other event |
|
|
Term
| conditonal probability formula |
|
Definition
| number of observations favoring event a and b / total number of observations favoring event b |
|
|
Term
|
Definition
| the likelihood of each of two events occuring |
|
|
Term
| joint probability formula |
|
Definition
| p(a,b)=number of observations favoring both event a and event b/total number of observations |
|
|
Term
|
Definition
| the likelihood of at least 1 of 2 events occuring |
|
|
Term
| adding probabilities formula |
|
Definition
| p(a or b) = p(a)+p(b) - p(a,b) |
|
|
Term
| sampling with replacement |
|
Definition
| returning the sampled case back to the population, allowing it to be chosen again |
|
|
Term
| sampling without replacement |
|
Definition
| selecting a case at random and then keeping it out of the population |
|
|
Term
| the two possible sampling situations: |
|
Definition
| sampling with replacement, sampling without replacement |
|
|
Term
|
Definition
| permutations and combinations |
|
|
Term
|
Definition
| an ordered sequence of a set of events (nPr) where n is the # of objects and r is the # of values in the sequence. ex (AB and BA are different AC and CA are different). Ordering matters. |
|
|
Term
|
Definition
| the ordering of a set of pairs is irrelevent. ex (BA is the same as AB) |
|
|
Term
|
Definition
| product of all positive integers less than or equal to n. ex: 3! = (3)(2)(1)=6 |
|
|
Term
|
Definition
determines the probability of successes across trials in situations where the trials are independent and each trial has only 2 possible outcomes.
probability of sucess =.500 and probability of failure= q= 1-p |
|
|
Term
| the binomial expression formula |
|
Definition
| p(r successes)={n!}/r!(n-r)! to the power of (p superscript r q superscript n-r) |
|
|
Term
| the mean of binomial distribution |
|
Definition
|
|
Term
| standard deviation of a binomial distribution |
|
Definition
|
|
Term
|
Definition
| the entire collection of events that you are interested in |
|
|
Term
|
Definition
| a subset of the population |
|
|
Term
|
Definition
| each member of the population has an equal chance of being included |
|
|
Term
| sampling error, why does it occur |
|
Definition
| will occur b/c sample data is only based on a portion of the population, so sample stats may differ from the value of its corresponding population parameter |
|
|
Term
|
Definition
| x - u (sample mean minus population mean) |
|
|
Term
|
Definition
| a sample mean is an unbiased estimator of the population mean. It is a statistic whose mean across all possible random samples of a given size equals the value of the population parameter. |
|
|
Term
| sampling distribution of the mean |
|
Definition
| the distribution of sample means over repeated sampling from one population |
|
|
Term
| characteristics explained by the central limit theorem |
|
Definition
1. the mean of the sampling distribution of the means will always equal the population mean.
2. standard error of the mean represents an average deviation of the sample means from the population means.
3.standard error of the mean gets smaller as the sample size increases and the variability of the scores in the population decreases
4. the sampling dist of the mean takes the shape of a normal distribution as the sample size gets larger. |
|
|
Term
|
Definition
| decisions are made concerning the values of parameters. key to inferential stats. it takes the data results and compares it to the population which allows you to make predictions based on the results. |
|
|
Term
|
Definition
| the difference between two population means is null or zero .. there is no diffference! symbol =h0. Need it because you can ever really prove something true. |
|
|
Term
|
Definition
| hypothesis that claims a difference between the two means, claims the difference is due to the independent variable. symbol = h1 |
|
|
Term
| four components of statistical power |
|
Definition
1. sample size: # of units studied
2. effect size: strength of the relationship between 2 variables.
3. alpha level: odds that the observed result is due to chance (normall is .05)
4. power: the odds that youll observe a treatment effect when it occurs |
|
|
Term
| a few ways to increase statistical power: |
|
Definition
| increase sample size, increase alpha level, use a one tailed test, strong research design. |
|
|
Term
|
Definition
| you reject the null hypothesis when it is true |
|
|
Term
|
Definition
| failing to reject the null hypothesis when it is false |
|
|
Term
|
Definition
| a result is due to chance if probability is greater than the alpha level, it is non-chance if less than the alpha level .. Its statistically significant! |
|
|
Term
| directional (one tailed) test |
|
Definition
| designed to detect extreme outcomes in only one specified direction of the distribution |
|
|
Term
| non directional (two tailed) test |
|
Definition
| designed to detect extreme outcomes in either direction of the distribution |
|
|
Term
|
Definition
| # of pieces of information that are free of eachother aka they cannot be deduced from one another. as degree of freedom increases so does accuracy. |
|
|
Term
| assumptions of the one sample t-test |
|
Definition
| 1. the sample is randomly and independently selected from the population. 2. the scores on the variable are normally distributed in the population |
|
|
Term
| if theres not enough power in your study which type of error might you make |
|
Definition
|
|
Term
| why must you subtract the joint probabilities of a and b when doing an adding probabilities problem? |
|
Definition
| So that you do not double-count your data |
|
|
Term
| the degrees of freedom in a one-sample t-test |
|
Definition
|
|
Term
|
Definition
|
|
Term
|
Definition
|
|
