stats

Cards (18)

    • Random Sampling
    A simple random sampling or random sampling is a selection of 𝑛 elements derived from a population 𝑁, which is the subject of the investigation or experiment,
  • A population refers to the entire group that is under study
    or investigation or group
  • A sample is a subset taken from a population
  • The normal curve or bell curve is a graph that represents the probability density function of the normal probability distribution.
    The normal curve is also called the Gaussian curve, named after the mathematician Carl Friedrich Gauss.
  • Lottery sampling (Simple random sampling)
    A sampling technique where every member of the
    population has an equal chance of being selected.
  • Systematic sampling
    A sampling technique in which members of the population are
    ordered in some way such as alphabetically or numerically
  • Cluster sampling
    It is sometimes called area sampling, the population is divided into groups or clusters,
  • Stratified random sampling
    A sampling procedure wherein the members of the population are
    grouped based on their homogeneity
  • Multi-stage sampling
    It is done using a combination of different sampling techniques.
  • Nonrandom Sampling Techniques
    is used when the sample is not a proportion of the population
  • Quota sampling
    • The researcher limits the number of his samples based on the required number of the subject under investigation.
  • Convenience sampling
    • The researcher conducts a study at his convenient time, preferred place, or venue.
  • Purposive sampling
    • It is used in very small sample sizes.
  • INFERENTIAL
    STATISTICS
    • It involves making inferences, predictions, or generalizations
    • ESTIMATION
    It is a process whereby we select a random sample from a population
  •  Point Estimates - a single value that best determines the proposed parameter value of the population.
  • INTERVAL ESTIMATION
    • also called a confidence interval
    • the interval of values that predicts where the true population parameter belongs
  • A sample is a subset taken from a population,