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Prob & Stats Ch.1

Chapter 1 Vocab and Concepts

Variable a characteristic or attribute that can assume different values
Data the values (measurements or observations) that the variables can assume
Random Variables Variables whose values are determined by chance
Data Set A collection of data values
Data Value (Datum) Each value in a data set
Statistics the science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data
Descriptive Statistics consists of the collection, organization, summarization, and presentation of data
Inferential Statistics consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables, and making predictions
Probability the chance of an event occurring
Population consists of all subjects that are being studied
Sample a group of subjects selected from a population
Hypothesis Testing a decision-making process for evaluating claims about a population based on information obtained from samples
Qualitative Variables variables that can be placed into distinct categories, according to some characteristic or attribute
Quantitative Variables numerical variables that can be ordered or ranked
Discrete Variables variables which assume values that can be counted
Continuous Variables variables which can assume an infinite number of values between any two specific values. Obtained by measuring and often include fractions and decimals
Measurement Scales four common types of these scales are nominal, ordinal, interval, and ratio
Nominal Level of Measurement classifies data into mutually exclusive (nonoverlapping), exhausting categories in which no order or ranking can be imposed on the data
Ordinal Level of Measurement classifies data into categories that can be ranked; however, precise differences between the ranks do not exist
Interval Level of Measurement ranks data, and precise differences between units of measure do exist; however there is no meaningful zero
Ratio Level of Measurement possesses all the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist when the same variable is measured on two different members of the population
Four Basic Sampling Techniques Random, Systematic, Stratified, & Cluster
Random Samples selected by using chance methods or random numbers
Systematic Samples obtained through numbering each subject of the population and then selecting every nth subject
Stratified Samples obtained by dividing the population into groups (called strata) according to some characteristic that is important to the study
Cluster Samples the population is divided into groups called clusters by some means such as geographic area or schools in a large school district, etc.
Convenience Sample uses subjects that are convenient
Observational Study the researcher merely observes what is happening or what has happened in the past and tries to draw conclusions based on these observations
Experimental Study the researcher manipulates one of the variables and tries to determine how the manipulation influences other variables
Quasi-Experimental Study when researchers use already intact groups if random assignment is not possible
Independent (Explanatory) Variable the variable being manipulated in an experimental study
Dependent (Outcome) Variable the resultant variable of an experimental study
Treatment Group the group that receives specific treatment in an experimental study
Control Group the group that receives no treatment in an experimental study
Hawthorne Effect discovered in 1924 when researchers found that the subjects who knew they were participating in an experimental study actually changed their behavior in ways that affected its results
Confounding Variable variable that influences the dependent/outcome variable but was not separated from the independent variable
Define statistics the science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data
Three examples of how statistics is used in everyday life. 1) Fields of human endeavor (2) Analyze results of a survey (3) Tool in scientific research to make decisions based on controlled experiments (4) Operations research, quality control estimation, & predictions
3 reasons to study statistics (1) Understand statistical studies (2) Conduct research, design experiments, make predictions, and communicate results (3) Become a better consumer
Branch areas of statistics Differential and Inferential. Differential statistics deals with the collection, organization, summarization, and presentation of data, whereas inferential statistics deals with generalizing from samples to populations and making predictions/inferences.
Examples of Variables Qualitative - gender, eye color, etc. Quantitative - age, height, weight. Discrete - #'s of something. Continuous - often decimals obtained by measuring.
Examples of each of the levels of measurement Nominal - Gender, Zip code, Eye color Ordinal - Competition rankings, a person's build, letter grades Interval -
Created by: tyjocun