STAT 166 1-3

• Sample is the subset of the population.
• Variable is the one that's measure or observe.

  It is asking "what do you want to ask"?
• Population is the 100% participants. 


  It is asking "who do you want to study"?
• Observation is the realized value of variable. 


  For example, obtaining the degree programs such BASOC, BAPHILO.
• Data is the collection of observation's totality.
• The two types of variables are: Qualitative and Quantitative. 


  Qualitative is the names/labels that cannot perform any operations. While Quantitative is the measurable or observable in numbers.
• The 4 levels of measurement are: Nominal, Ordinal, Interval, and Ratio. 


  Nominal and ordinal is qualitative. Nominal has categories and is equal importance. Ordinal has rankings.
• Interval's 0 is not absent at all since it has characteristic. Ratio's 0 has absolute value and can be menaingfully calculated.
• Interval is a fixed unit of measurement. 


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• Parameter describes population. 


  Statistic describes only the sample of the population.
• Two types of statistics: Descriptive and inferential. 


  Descriptive simply describes while inferential makes generalizations.
• Statistical inquiry is designed research that provides data.


  Concerned with data.
• 5 methods of data collection: Observation, Experiment, use of documented data, registration, and survey. 


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• Observation uses senses and devices. It happens in naturalistic setting. 


  Experiment has direct human intervention and comparison.
• Use of documented data uses previous studies. It is governed of national offices and agencies.
• Registration records the vital statistics. 


  Survey obtains data directly from participants.
• 4 methods of conducting a survey: Personal interview, telephone interview, online surveys, and focus group discussion. 


  "Mode effect" is the caution in mixed collection methods.
• 2 stages of survey work: Census and sample survey. 


  Census are the 100% population. Sample survey is only the subset of population.
• Sampling is the process of getting a sample. 


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• 2 types of error in survey: Sampling error and non-sampling error. 


  Sampling error comes from the sample. Non-sampling error comes from the human.
• Target population is the GENERAL participants. 


  Survey population is the SPECIFIC/adjective-based participants.
• Sampling frame is the LIST OF survey population.
• 2 types of Sampling Method: (1) Probability sampling; (2) Non-probability sampling.
• 4 types of probability sampling: (1) Simple random sampling; (2) Stratified sampling; (3) Systematic sampling; (4) Cluster sampling.
• 4 types of non-probability sampling: (1) purposive sampling; (2) convenience sampling; (3)quota sampling; (4) snowball sampling.
• Simple random sampling randomly selects participants from a total population. Each member of the population has an equal chance of being selected. 


  Con: not well-represented.
• Stratified sampling divides the population into strata to have each representative. 


  Occurs in homogeneous population.
• Systematic sampling randomly first selects to generate pattern. 


  No repeated factor.
• Cluster sampling is similar to stratified but only differs on heterogeneous population.
• Purposive sampling includes preliminary presumptions on target participants. Personal criteria involves.
• Convenience sampling is a voluntary, accidental, or random sampling. 


  E.g., online survey, people walking on the streets, etc.
• Quota sampling selects predetermined number of participants. Such number is already made.
• Snowball sampling is a referral sampling. Someone refers you to others to gather other participants.
• Non-probability sampling has bias. No equal chance to being selected. 


  Probability sampling has systematic procedures. The inferences are valid.
• Population


  A collection of all the elements under consideration in any statistical study
• Sample


  A part (or subset) of the population from which information is collected
• Variable


  Characteristic or attribute of the elements in a collection that can assume different values for different elements
• Observation


  Realized value of a variable
• Data


  The collection of observations
• Qualitative Variable


  Have labels or names assigned to their respective categories, assumes values that are not numerical but can be categorized