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Statistics Cheat Sheet

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Statistic- is a number computed from a sample of data. It is characteristic of a sample. A summary measure that is computed from a sample to describe a characteristic. (Numerical summary of the population) (Ex. The proportion of females randomly selected from the registered voters of a county or the average time it takes for the first 5 students to complete an exam)
Parameter- A characteristic (numerical summary) of the entire population. A number computed from the entire population usually unobservable.
Subject- the entities that we measure in a study. Population- the collection of all subjects under study.
Proportion- of the observations that fall in a certain category is the frequency (count) of observations in that category divided by the total number of observations. Proportion and percentages (aka relative frequencies) Probability- the chance that an even will occur.
Sample- a subset of the population. Random Samples are most valid. Design- Plan for how the data will be collected.
Two events are dependent if the outcome or occurrence of the first affects the outcome or occurrence of the second so that the probability is changed.
Sample Space- set of all possible outcomes for a random phenomenon Variables (COLUMNS)- characteristics or measurements on the subject.
Event-subset of the sample space Description- summarizing the data that are obtained.
Descriptive Statistics- methods for summarizing the data. Usually consists of bar graphs and numbers like averages and %’s.
Inference- Making conclusions (predictions) about the population based on the data collected (Inferential Statistics). Observation (ROW)- subject Categorical Data- defines categories for subjects (groups) uses frequencies {counts}, percent’s and frequency tables.
Quantitative Data- numerical data (ex. Pulse rate) Ordinal Data- ordered categories

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