Statistics

• Statistics- the science of collecting, presenting, interpreting, and analyzing data for effective decisions.
• Population- the entry or totality of objects, things, or persons under study.
• Sample- a subset taken from the population.
• Parameter- numerical measures or characteristics of the population.
• Statistic - numerical measure or characteristic of the sample.
• Variable - a characteristic or property whereby the members of the group differ from one another.
• Constant - a characteristic or property whereby the members of the group do not differ from one another.
• Statistics can give precise description of the data.
• Statistics can predict the behavior of individuals
• Statistics can can used to test the hypothesis
• Statistics can be used in decision making in any field
• Suspect samples- use very small sample to obtain information
• Ambiguous averages - common measures that are loosely called averages are mean, median, mode and midrange
• Changing the subject - different values are used to represent the data set
• Detached Statistics - one in comparison with no comparison is made
• Implied connections - attempt to imply connections between variables that may not actually exist.
• Misleading graphs-  graphs give visual representation of data that enables the viewers to analyze and interpret data more easily than by simply looking the numbers. Can misrepresent the data and lead the reader to false conclusions.
• Faulty survey questions -  be sure that the questions are properly written since the way questions are phrased can often influence the way people answer them.
• 3 types of statistics - nature, characteristics, sources
• Nature - qualitative, quantitative
• Characteristics - discrete, continuous
• Sources - primary, secondary
• Nominal -  data that consists of names, labels, classifications and categories only.
• Ordinal - data may be arrange in some order but differences between data values cannot be determined or meaningless
• Interval- same as the ordinal, with additional, property that we can determine meaningful amounts of differences between the data.
• Ratio - an interval level modified to include the inherent zero starting point.
• Classification of Statistics - Descriptive, Inferential
• Descriptive Statistics – a manner of organizing, presenting or summarizing a set of data or observations in an informative way.
• Inferential Statistics -  uses sample data to make inferences about a population.
• Sampling – is the act, process, or technique of selecting an appropriate sample, or representative part of a population to determine the characteristics of the whole population.
• Random Sampling/Scientific Sampling – a process whose members have an equal chance of being selected from the population; it is also called probability or scientific sampling
• Non-Random Sampling/Non-Scientific Sampling – a sampling procedure where samples selected in a deliberate manner with little or no attention to randomization; it is also called non-probability or non-scientific sampling
• Simple Random Sampling – is a process of selecting n sample size in the population. It is commonly used sampling technique.
• Systematic Sampling – is a random sampling technique which considers every nth element of the population in the sample with the selected random starting point from the first q members.
• Stratified Sampling – a given population is purposely divided into homogenous partitions (groups) depending on certain factors that might be affecting the results of this study. These homogenous partitions are also called strata.
• Cluster Sampling - grouping the respondents according to their geographical location
• 1. Convenience Sampling/haphazard sampling - samples taken are readily available to participate in the study.
• Purposive Sampling - sampling is done with a purpose in mind.
• Quota Sampling - is the equivalent of stratified random sampling in terms of non-probability sampling.
• Snowball Sampling - is sometimes called chain referral sampling.