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Definition
| The set that consists of all the subjects of interest |
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The researcher observes values of the response variable and explanatory variables for the sampled subjects, without
anything being done to the subjects (such as imposing a treatment) |
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Type of observational study. A sample
survey selects a sample of people from a population and interviews them
to collect data. |
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Assigning subjects to certain
experimental conditions and then observing outcomes on the response
variable. The experimental conditions, which correspond to assigned values of the explanatory variable, are called treatments. |
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| Is observational or experimental better? Why? |
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Definition
An experiment reduces the potential for lurking variables to a ffect the result. Thus, an experiment gives the researcher more control over outside infuences.
Also, notice that we can not determine cause and e ffect merely from an observational study. Remember that association does not imply causation. Hence, cause and e ect can only be established through rigorous experimentation.
Unfortunately, experiments are not always possible due to ethical reasons,
time considerations and other factors. Therefore, it is important to do
observational studies properly. |
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Definition
| List of subjects in the population from which the sample is taken, ideally it lists the entire population of interest |
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The best way of obtaining a sample that is
representative of the population |
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| Simple random sampling (SRS) |
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Definition
| Each possible sample of that size has the same chance of being selected |
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| Tells how well the sample estimate predicts the population percentage (1/sqrt n * 100%) |
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Type of sample survey that is easy to obtain. Some problems with convenience samples are:
- Unlikely to be representative of the population.
- Often severe biases result from such a sample.
- Results apply ONLY to the observed subjects. |
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Definition
| The subjects volunteer to be part of it. Volunteers do not tend to be representative of the entire population. Type of convenience sample |
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Definition
Tendency to systematically favor certain parts of the population over
others. |
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| Bias resulting from the sampling method such as using nonrandom samples or having under-coverage. |
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| Occurs when some sampled subjects cannot be reached or refuse to participate or fail to answer some questions. |
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| Occurs when the subject gives an incorrect response or the question is misleading. |
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| The subjects of an experiment; the entities that we measure in an experiment. |
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A specific experimental condition imposed on the subjects of the study; the treatments correspond to assigned values
of the explanatory variable. |
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Definition
Defi nes the groups to be compared with
respect to values on the response variable. |
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The outcome measured on the subjects to
reveal the e ffect of the treatment(s). |
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Allows the researcher to analyze the
e ffectiveness of the primary treatment. |
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Definition
| It helps to eliminate the e ffects of lurking variables and confounding, and also helps to reduce researcher bias. |
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Definition
| Allows us to attribute observed e ffects to the treatments rather than ordinary variability. |
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| Main components of a good experiment |
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Definition
| Randomization, replication, control/comparison group |
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Definition
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Definition
| An improvement in health due not to any treatment but only to the patient's belief that he or she will improve. |
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| 3 things randomly assigning subjects does |
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Definition
-Eliminate bias that may result from the researcher assigning the subjects.
-Balance the groups on variables known to aff ect the response.
-Balance the groups on lurking variables that may be unknown to the
researcher. |
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Term
| 3 things replication does |
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Definition
-The di fference due to ordinary variation is smaller with larger samples.
-We have more confin dence that the sample results reflect a true diff erence due to treatments when the sample size is large.
-Since it is always possible that the observed eff ects were due to chance alone, replicating the experiment also builds con fidence in
our conclusions. |
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Definition
Neither the subjects nor the investigators working with them know which treatment each subject
is receiving |
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| Double-blind controls what type of bias? |
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Definition
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| 3 types of observational study? |
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Definition
| Sample, retrospective, prospective |
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Definition
| Attempts to take a cross section of a population at the current time |
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Definition
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| Follows subjects into the future |
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| 3 forms of randomization sample surveys use |
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Definition
| Simple random sampling, clustered sampling, and stratified random sampling |
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Definition
| A retrospective observational study in which subjects who have a response outcome of interest (the cases) and subjects who have the other response outcome (the controls) are matched and compared on an explanatory variable. |
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Definition
| Categorical explanatory variables in an experiment |
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Definition
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Definition
| Uses a single experiment to analyze the effects of two or more explanatory variables on the response. |
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Definition
The subjects receiving the two treatments
are somehow matched |
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Definition
| The same individual is used for the two treatments. |
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Definition
| The generalization of the matched pairs design, extended to three or more treatments. Each set of matched experimental units is then called a block. |
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Definition
| As the number of (independent) trials increase, the proportion of occurrences of any given outcome approaches a particular number in the "long run". |
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Definition
| The proportion of times that the outcome would occur in a long run of observations. |
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Definition
| Diff erent trials of a random phenomenon are independent if the outcome of any one trial is not aff ected by the outcome of any other. |
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Definition
The long run proportion of times that the outcome occurs in a very large number of trials. Unfortunately, this is not always helpful or possible, because
sometimes we can not observe "repetitions" of the experiment. |
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Term
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Definition
| Your degree of belief that the outcome will occur based on the information available. |
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| A branch of statistics that uses subjective probability as its foundation. |
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Definition
| Are not in some other event |
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| Intersection of two events |
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Definition
| Are in one event and in another event |
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Definition
| Are in one event or in another event |
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Definition
| If A and B do not have any common outcomes. That is, if their intersection is empty. |
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Definition
A and B, consists of the outcomes that are in A or B. Notice that this include the outcomes that are in both, A and
B. We write A U B. |
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Term
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Definition
| P(A or B) = P(A) + P(B) - P(A and B) |
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Definition
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| Multiplication rule (two independent events intersecting) |
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Definition
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Definition
| The probability that one occurs is not affected by the occurrence of the other event. |
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Definition
| A numerical measurement of the outcome of a random phenomenon |
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Term
| Probability distribution of a random variable |
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Definition
| Speci es its possible values and their respective probabilities |
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Term
| Probability distribution of a discrete random variable |
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Definition
-For each x, the probability P(x) falls between 0 and 1.
-The sum of the probabilities for all the possible values of x is equal
to 1. |
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Term
| Probability density function |
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Definition
-Each interval has probability between 0 and 1. The probability corresponds to the area under the curve, above the interval.
-The interval containing all possible values has probability equal to 1, so the total area under the curve always equals 1. |
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Definition
| Bell-shaped and characterized by its mean and standard deviation |
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Term
| Why normal distribution is important |
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Definition
-Many distributions have an approximate normal distribution.
-Approximates many discrete distributions well when there are a large number of possible outcomes.
-Many statistical methods use it even when the data are not bell shaped |
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Term
| Z score for a value of x of a random variable |
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Definition
| The number of standard deviations that x falls from the mean. |
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Term
| Z score for a value of x of a random variable |
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Definition
| The number of standard deviations that x falls from the mean. |
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Term
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Definition
| Has one of two possible outcome |
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Term
| Conditions for the Binomial Distribution |
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Definition
-Each of n trials has two possible outcomes: The outcome of interest is called success and the other outcome is called failure.
-Each trial has the same probability of observing a "success". This
probability is denoted by p.
-The n trials are independent. |
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Term
When the number of trials n is large enough so that np and n(1 - p) are
both at least 15, then the binomial distribution can be well approximated by a normal distribution with mean np and standard deviation sqrt (np(1-p)) |
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Definition
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