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| The analysis of medical, biological and public health data (applicable to epidemiology, policy, community, environmental health, and occupational health) |
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| The science in which inferences are made about specific random phenomena on the basis of relatively limited sample material. |
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| Statistics that summarize information. |
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| Statistics that make a decision. |
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| The largest collection of entities in which we are interested and that have a common observable characteristic. (Can be finite OR infinite) |
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| A characteristic of a population. (A fixed value that represents a characteristic in a population.) |
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| A characteristic that takes on different values for different persons, places, or things. |
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| A variable that uses categories only (ie: gender, grade in school...) |
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| A variable that can be measured (ie: height, weight, amount of water in pipes...etc) |
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| A value that arises as a result of chance factors. |
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| A variable that only takes certain values. There are gaps between the values. |
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| A discrete, qualitative variable that can take on only two values. |
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| A quantitative variable that has an infinite number of possible values. There are no gaps between values. |
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| A measure from a sample used to estimate a parameter. |
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| Putting into non-overlapping categories. Classification based on a qualitative assessment; no information regarding quantity or amount. (ie. gender, ABO blood group, country of birth...etc) |
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| Putting into non-overlapping categories based on qualitative data including the concept of a "greater than" or "less than" ranking. (ie. grade in school, "how do you feel today?"...etc) |
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| Has no true zero point. 0 is just another point on the scale. (ie. temperature) |
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| Has a true zero point with a physical significance (ie. blood pressure level, height, weight...etc) |
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| A sample in which every possible observation in the population has an equal chance of being selected for the sample. (Can be either "with replacement"-meaning the observation can be reseen even after being seen already OR "without replacement"-meaning the observation cannot be seen twice before all observations are seen once) |
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| Value that occurs most often. (EX1: If each observation is observed twice, this does not exist in the sample. EX2: If each observation is observed twice except one, then ALL OBSERVATIONS SEEN TWICE are this. EX3: If 2 observations are seen 3X and all other observations are seen 2X or less, than the 2 observations seen 3X are BOTH considered this) |
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| Middle value. Value that divides the dataset into two equal parts. |
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| The difference between the largest and smallest values of a dataset. |
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| The difference between the upper and lower 25th percentile. |
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| Allows for comparison of datasets. |
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| The set of all possible outcomes. |
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| The relative frequency of the event over a large number of trials. |
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| The probability that at least one of those two events occur. |
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| Intersection of two events |
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| Probability that both events occur. |
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| The probability of that event NOT happening. |
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| Two events are independent. |
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| Is true only if the outcome of one event does not impact that of the other event. |
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| Events that cannot occur at the same time. |
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| The risk of an event relative to another event. (Is equal to 1 if both events are independent.) |
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| Predictive Value Positive |
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| The probability that a person as a disease given the test is positive |
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| Predictive Value Negative |
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| Probability that a person does not have a disease given the test is negative |
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| The test is positive but true status is no disease |
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| Test is negative but true status is disease is present |
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| Probability symptom is present given the subject has a disease |
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| Probability symptom is not present given subject does not have disease |
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| Probability of having a disease regardless of how long a person has had the disease |
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| Probability that a person without disease develops desease in a specified time period |
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| A numeric function that assigns probabilities to different events in a sample space |
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| Specific values with specific probabilities |
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| Probability Mass Function |
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| AKA Probability Distribution - A rule to assign possible values for a discrete random variable, X |
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| The number of ways of selecting "k" items out of "n," when the order IS important |
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| the number of ways of selecting "k" objects out of "n," when order does NOT matter |
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| n number of independent Bournoulli trials, each with only two possible outcomes |
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| Means "everything in between" |
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