Unit 1: Statistics, Data, & Statistical Thinking

statistics

the science of data, this involves collecting, classifying, summarizing, organizing, analyzing, presenting and interpreting numerical information

experimental

an object (person, thing, event) about which we collect data

population

a set of units (people, objects, events) that we are interested in studying

variable

a characteristics or property of an individual experimental unit in the population

sample

a subset of the units in a population

statistical inference

an estimate, prediction, or some other generalization about a population based on information contained in a sample

Measure of reliability

a statement (usually quantitative) about the degree of uncertainty associated with a statistical inference

descriptive statistics

utilizes numerical and graphical methods to look for patterns in a data set, to summarize the information revealed in a data set, and to present that information in a convenient form

Inferential statistics

utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data

quantitative data

measurements that are recorded on a naturally occurring numerical scale

qualitative data

measurements that cannot be measured on a natural numerical scale; they can only be classified into one a group of catergories

designed experiment

data collection method where the researcher exerts full control over the characteristics of the experimental units sampled. These experiments typically involve a group of experimental units that are assigned the treatment and an untreated group

observational study

a data collection method where the experiment units sampled are observed in their natural setting

representative sample

exhibits characteristics typical of those possessed by the target population

simple random sample

sample of n experimental units is a sample selected from the population in such a way that every different sample of size b has an equal chance of selection

selection bias

results when a subset of the experimental units in the population is excluded so that these units have no chance of being selected in the sample

non response bias

results when the researchers conducting a survey or study are unable to obtain data on all experimental units selected for the sample

measurement error

refers to inaccuracies in the values of the data recorded