descriptive statistics – Collection of methods for organizing, displaying, and describing data, tables, and summary measures.

inferential statistics – Collection of methods based on sample results to make decisions for the population.

open source – A software program in which the source code is available to the general public for use and/or modification from its original design free of charge.

parameter – A summary measure that describes characteristics of an entire population.

population – An entire set of items or things under consideration

R – An open source computer language that allows the user to program algorithms to produce statistical analysis and visualization.

sample – The portion of the population that is selected for analysis.

spreadsheet – A data listing on paper or computer that has rows and columns for recording data.

spreadsheet applications – Computer programs that let you create and manipulate tabular, organized data electronically.

statistic – A summary measure computed from sample data that is used to describe the entire population.

statistics – Group of methods used to collect, analyze, present, and interpret data to make decisions

variable – A characteristic under study that assumes different values for different elements

lternative testing – This evaluates the hypothesis, denoted by H1 or Ha, that sample observations are influenced by some non-random cause

bivariate data – This is when the research study focuses on the relationship between two variables.

continuous variable – These are numerical responses that arise from a measuring process.

correlation research – Research that tests for statistical relationships between two or more variables

discrete variable – This produces a numerical response that arises from a counting process.

hypothesis testing – A process, by which an analyst tests a statistical finding, with the goal of either to accept or to reject the null hypothesis. The methodology employed by the analyst depends on the nature of the

data used, and the goals of the analysis.

inter-rater test – This process asks independent judges to examine your variables and compare their results for consistency.

instrument – For the purposes of this book, is a formula that has already been proven and used by many in statistical analysis.

null hypothesis – A statistical hypothesis to be tested

observation research – Type of research in which researcher observes ongoing behavior

quantitative variable – A variable that is measured based on a numeric values.

qualitative variable – Also known as categorical variables take on values and names or labels.

quasi-experiment – A research design which lacks the full control of a true experiment design. The treatment variable often occurs naturally,but sometimes the researcher may be able to manipulate it.

reliability – The consistency of the measurement instrument

research problem – A statement about an area of concern, a condition to be improved, a difficulty to be eliminated, or a troubling question that exists in scholarly literature, in theory, or in practice that point to the

need for meaningful understanding and deliberate investigation. In some social science disciplines the research problem is typically posed in the form of a question.

research process – Seven steps in the research procedures thatinclude understanding the nature of the problem, deciding what to measure, data collection, data analysis, formal data analysis, visualization, and

results.

split-half test – The test of consistency of the instrument in two different times

test-retest – The test of the consistency of the instrument over time.

true experiments – Research that focuses on one variable under a close environment and setting

Type I error – Occurs when the researcher rejects a null hypothesiswhen it is true.

Type II error – Is the failure to reject a false null hypothesis

univariate data -When the research study focuses on just one variable

validity – Accuracy of measurement, or legitimacy of the measurement