### random sample

requires (1) each individual in the population has an equal chance of being selected and (2) the probabilities must stay constant from one selection to the next if more than one individual is selected; it ensures there is no bias

### sampling with replacement

ensures that the probability is not changing from one selection to the next

### normal distribution

the commonly occuring shape for a population distribution which is symmetrical, with the mode in the middle and frequencies tapering off as you move towards either extreme

### How can normal distribution be used to estimate probability?

when given the mean and standard deviation, we can use this information with the proportions for a normal distribution. Then we can determine the probabilities associated with specific samples by first turning the probability question into a proportion question

### sampling error

the natural discrepancy or amount of error between a sample statistic and its corresponding population parameter

### sampling distribution

a distribution of statistics obtained by selecting all the possible samples of a specific size from the population

### distribution of sample means

the collection of sample means for all the possible random samples of a particular size (n) that can be obtained from a population

### Central Limit Theorem

provides a precise description of the distribution that would be obtained if you selected every sample mean and consructed the distribution of the sample mean

### hypothesis test

a statistical method that uses the data to evaluate a hypothesis about a population to see whether the treatment has an effect on the individuals in the population

### null hypothesis

predicts that the treatment has no effect on the scores for the population and states that in the general population there is no impacts

### alternative hypothesis

predicts that the treatment does indeed have an effect on the dependent variable and that there is an impact for the general population

### chance probablity

the probabilty that your empirical results could be due to chance WHEN YOUR NULL HYPOTHESIS IS TRUE

### critical value

The value of a statistic required in order to consider the results significant that leads us to reject Ho

### Type I Error

reject Ho when Ho is true; saying the treatment has effect when it does not (false research published)

### Type II Error

fail to reject Ho when Ho is false; study fails to detect a treatment effect that exists

### statistical power

the probability of correctly rejecting Ho when false (1-ß=power); pre-defined by study investigators to reduce risk of type II error

### one tailed test

A one-tailed test will test either if the mean is significantly greater than x or if the mean is significantly less than x