{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Exam II review

Exam II review - Probability-the probability of an event is...

This preview shows pages 1–2. Sign up to view the full content.

Probability—the probability of an event is the proportion of times we would expect the event to occur in an infinitely long series of identical sampling experiments If all the possible outcomes are equally likely, the probability of the occurance of an event is equal to the proportion of the possible outcomes characterized by the event Confidence statement: Statistic + Margin of error Margin of error = 1/ n 1/2 Confidence interval: a range of values constructed from sample data so the parameter occurs within the range at a specified probability. The specified level of probability is called the level of confidence Confidence interval for a sample mean: X + Z (S/N 1/2 ) Confidence interval for a sample proportion: p + Z [(p(1-p))/n] 0.5 A value, computed from sample information that is used to estimate the population parameter Standard error of the sample mean—the standard deviation of the sampling distribution of the sample means. It is a measure of the variability of the sampling distribution of the sample mean Experimental process: o Subjects treatment observation Variables o Explanatory variable (independent variable) o Response variable (dependent variable) o Lurking or confounding variable Alternative experimental designs o Completely randomized design- simplest design strategy; each subject is randomly assigned to one group; typically, group sizes are identical o Block design—used when known extraneous variables may influence the experiment; subjects are pre-sorted by the influencing variables, then partitioned into similar blocks; subjects from each block randomly assigned to groups o Matched pairs design—each subject receives each treatment; treatment sequence is randomly chosen for each subject o Double blind design—neither the subjects nor the investigators know which treatment is administered Control—minimize the effects of lurking/confounding variables on the response, most simply by comparing several treatments Randomize—use impersonal chance to assign subjects to treatments Replicate—repeat the experiment on many subjects to reduce chance variation in the results Statistical significance—an observed effect so large that it would rarely occur by chance Sampling frame: the list of units from which a sample is chosen Built in bias o Convenience sample—sample where the patients are selected, in part or in whole, at the convenience of the researcher o Voluntary response sample –consists of people who chose themselves by responding to a general appeal. They often over represent people w/ strong opinions, most often negative opinions. Simple Random Sample (SRS)—A sample of N units from the sampling frame chosen in such a way that every possible group of N units has the same chance of being chosen o Random: fair, representative, unbiased o Random sample designs: simple; multi-stage; systematic; stratified; cluster; hybrid o Possible shortcomings: bias due to poor sampling frame, cost of sampling

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

Page1 / 6

Exam II review - Probability-the probability of an event is...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online