STATS & PROB

• Statistics is a collection of methods for planning experiments, obtaining data, and then analyzing, interpreting and drawing conclusions based on the data.
• Variable is a characteristics that is observable or measurable in every unit of universe.
• Data are the values that the variables can assume. It is also the body of information or observations being considered by the researchers.
• Population is the set of all possible values of a variable.
• Sample is a subgroup/subset of a population.
• Descriptive Statistics are used to say something or describe a set of information collected. It can be represented with graphs.
• Inferential Statistics are used to say something about a larger group (population) using information collected from a small part of that population (sample).
• Qualitative Variables - words or codes that represents a class or category.
• Nominal Level - This is characterized by data that consists of names, labels, or categories only.
• Ordinal Level - This involves data that arranged in some order, but differences between data.
• Quantitative Variables - These are variables that are classified according to numerical characteristics.
• Continuous Variables - It can assume all values between any two specific values. (0.5, 1.2, etc.). Data are obtained by measuring.
• Probability - The prediction of a certain outcome when something occurs. Deals with chances or possibilities.
• Trial - Is the repetition of an experiment.
• Outcome - Is the result of an experiment.
• Sample Space - It contains all possible outcomes in an experiments.
• Random Variables - Set of numbers assigned to the outcome of an experiment. Denoted by X.
• Mean - characterizes the position of the curve.
• Standard Deviation - Characterizes the spread of the curve.
• Parameter - is a descriptive measure computed from an entire population of data.
• Statistic - is descriptive measure computed from a sample data.
• Probability Sampling - it refers to the selection of a sample from population, when this selection is based on the principle of randomization or chance.
• Simple Random Sampling – Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample.
• Systematic Sampling - this is done by numbering each subject of the population and then selecting nth number.
• Stratified Random Sampling – this done by creating strata (subgroups) in a population according to various factors.
• Cluster Sampling - this method uses intact groups called clusters.