Statistics

• N


  Population size
• n


  sample size
• Population


  it consists of all members of the group about which you want to draw
• Sample


  a portion or a part of the population of interest selected for analysis
• Random Sampling


  it is a sampling method of choosing representatives from the population wherein every sample has an equal chance of being selected
• Probability Sampling


  it involves random selection
• Non Probability Sampling


  it doesn't involve random selection of data
• Simple Random Sampling


  most commonly used sampling technique in which every respondent has an equal probability of being selected
• Systematic Random Sampling


  often used on long population lists, in order to determine the interval, the formula K=N/n should be use
• Stratified Random Sampling


  it involves dividing the population into groups, called strata, depending on certain characteristics that are relevant to the study (such as age, gender, income level, etc.) and choosing a respondent from each strata
• Cluster Sampling


  it involves dividing the population into clusters based on their geographic location, organizational structure, or some other naturally occurring grouping, and randomly selecting a respondent from each cluster
• Convenience Sampling


  it involves gathering data from nearby sources
• Purposive Sampling


  it involves deliberately selecting participants who possess specific characteristics or experiences relevant to the research question
• Snowball Sampling


  sometimes called chain-referral sampling. a sampling in which the respondent is asked to give recommendations of referrals to possible respondents
• Volunteer Sampling


  in which a respondent is volunteering to answer the research questions
• Quota Sampling


  in which the sample units are picked for convenience but certain quotas are given to interviewees
• Sloven Formula


  $n=$$N/1+$$Ne^2$
• Parameter


  the measurement or quantity that describes the population
• Statistics


  the measurement or quantity that describes the sample
• MEAN (statistics)

  
• PARAMETER

  
• Sampling Distribution of Sample Mean

  a frequency distribution using the means computed from all possible random samples of a specific size taken from a population
• Sampling Error

  the difference between the sample mean and the population
• First step in constructing the sampling distribution of the means


  Determine the number of sets of all possible samples that can be drawn from the given population by using the population "NCn"
• Second step in constructing the sampling distribution of the means


  List all the possible samples and compute the mean of each
• Third step in constructing the sampling distribution of the means


  construct the sampling distribution
• estimate

  the value or range values that approximates the population value
• estimation

  the process of determining parameter values
• mean

  also known as the average computed from the table
• parameter

  the number that describes population
• statistics

  the number that describes the sample
• Point estimate

  a specific numerical value of a population parameter, best estimate of a population mean
• Interval estimate

  range or values used to estimate a parameter, the estimate may or may not contain the true parameter values
• Three types of estimation

  unbiased, negative bias, and positive bias
• Unbiased


  estimate is within the value of the mean
• Negative Bias


  estimate is below the value of the mean
• Positive Bias


  estimate is above the value of the mean
• Critical values

  also known as confidence coefficients, the z-values that is used in describing the characteristics of a target population
• 90% confidence level

  z= +/- 1.65 is used
• 95% confidence level


  z= +/- 1.96 is used