STATS EXAM

• statistics - It is a branch of applied mathematics
• probability - branch of mathematics that deals with the occurrence of a random event.
• random variable is a function that associates a real numberrandom
• discrete random variable if its set of possible outcomes is countable.
• continuous random variable if it takes on values on a continuous scale
• Classify the following random variables as discrete or continuous.

  1. The number of defective computers produced by a manufacturer.

  2. The weights of newborns each year in a hospital.

  3. The number of siblings in a family of a region.

  4. The amount of paint utilized in a building project.

  5. The number of dropout in a school district for a period of 10 years.

  6. The number of workers in the University of Mindanao.

  
  

  7. The number of school drop – outs in Davao City.

  
  

  8. The speed of a car.

  
  

  9. The length of the Nile river.
• A normal distribution curve is a bell – shaped.
• The mean is considered as a measure of the “central location”
• variance is a measurement of the spread
• Standard Deviation is the measurement of the dispersion
• When the standard deviation is large, the normal curve is short and wide, while a small value for the standard deviation yields skinnier and taller graph.
• The empirical rule is also referred as the 68-95-99.7% rule
• POPULATION - The set of all possible values of a variable
• SAMPLE – It consists of one or more data drawn from the population
• RANDOM SAMPLING – It is a sampling method of choosing representatives from the population wherein every sample has an equal chance of being selected. Accurate data can be collected using random sampling techniques.
• PROBABILITY SAMPLING – The sampling techniques that involve random selection.
• NON – PROBABILITY SAMPLING – The sampling techniques that do not involve random selection of data.
• Simple Random Sampling - It is the most basic random sampling wherein each element in the population has an equal probability of being selected.
• SYSTEMATIC RANDOM SAMPLING - listing all elements in the population and selecting every interval in the population list.
• STATRATIFIED RANDOM SAMPLING - random sampling wherein the population is divided into different strata or divisions.
• CLUSTER SAMPLING - random sampling wherein population is divided into clusters or groups and then the clusters are randomly selected.
• CONVENIENCE SAMPLING - researcher gathers data from nearby sources of information exerting minimal effort
• SNOWBALL SAMPLING - Also called chain – referral sampling, it is defined as a non – probability sampling technique in which the samples have traits that are rare to find.
• PARAMETER - The measurement or quantity that describes the population.
• STATISTIC - The measurement or quantity that describes the sample.
• Quota Sampling - It is where sample units are picked for convenience but certain quotas are given to interviewers.