RESERCH, Data and quati analysis

• Quantitative Data Interpretation — refers to a precesses by which numerical data is analyzed
• Univariate Analysis — Test a single variable to determine whether similar the sample population is to the population from which it has been drawn.
• Bivariate — Test two variables on how they differ with each other.
• Multivariate — Test three or more independent variables at a time on the degree of relationship with the dependent variable.
• Status Analysis — stresses real fact relating to current conditions in a group of subjects chosen for study.
• Cost-Effective Analysis — applicable in comparing the cost between two or more variables, and to determine which of the variables is most effective.
• Variance — average of the squared differences from the mean.
• Variance — measure of dispersion, meaning it is a measure of how far a set of numbers is spread out from their average value.
• Standard Deviation — statistic measuring the dispersion of a dataset relative to its mean and is calculated as the square root of the variance.
• Descriptive Analysis — The first level of analysis, this helps researchers find absolute numbers to summarize individual variables and find patterns.
• Inferential Analysis — These complex analyses show the relationships between multiple variables to generalize results and make predictions.
• Data analysis


  A process that involves examining and investigating collected data for interpretation to discover relevant information, drawing or proposing conclusions, and supporting decision making to solve a research problem
• Nominal scale


  A scale used to label variables that have no quantitative values
• Ordinal scale


  A scale used to label variables that have a natural order, but no quantifiable difference between values
• Interval scale


  A scale used to label variables that have a natural order and a quantifiable difference between values, but no "true zero" value
• Ratio scale


  A scale used to label variables that have a natural order, a quantifiable difference between values, and a "true zero" value
• Statistics


  The collection of numerical facts that are expressed in terms of summarizing statements and that have been collected from several observations or from other numerical data
• Regression analysis


  A set of statistical methods used for the estimation of relationships between a dependent variable and one or more independent variables. It can be utilized to assess the strength of the relationship between variables and for modeling the future relationship between them
• Data interpretation


  The implementation of processes through which data is reviewed for the purpose of arriving at an informed conclusion
• Statistical modeling


  The process of describing the connections between variables in a dataset using mathematical equations and statistical approaches. In statistical modeling, we use a collection of statistical methods to investigate the connections between variables and uncover patterns in data