Stats01

• What is the definition of statistics?

  Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data.
• How does statistics contribute to decision-making?

  Statistics helps in the process of making decisions efficiently by analyzing and interpreting numerical data.
• What are the two main branches of statistics?

  1. Descriptive Statistics
  2. Inferential Statistics
• What is the purpose of descriptive statistics?

  Descriptive statistics provides an overview of the information gathered through numerical measurements, charts, graphs, and tables.
• What does inferential statistics do?

  Inferential statistics uses methods to extend results obtained from a sample to the population and measures the reliability of those results.
• What is a population in statistics?

  A population refers to a large amount of data or the set of all possible values of the variables.
• Why is a sample used instead of a population?

  A sample is used because making a census or complete enumeration of a population would be impractical or impossible.
• What are qualitative variables?


  Qualitative variables describe certain types of information and provide items in various qualities or categories.
• Give examples of qualitative variables.


  Examples of qualitative variables include name, gender, address, religion, and program.
• What defines quantitative variables?


  Quantitative variables measure or identify population or sample based on a numerical scale.
• How can quantitative variables be analyzed?

  Quantitative variables can be analyzed using statistical methods and illustrated using diagrams such as tables, graphs, and histograms.
• What are the two classifications of quantitative variables?

  1. Discrete Variables
  2. Continuous Variables
• What is a discrete variable?


  A discrete variable can assume a finite or countably infinite number of values, usually measured by counting.
• Provide examples of discrete variables.


  Examples of discrete variables include the number of children in a family and the number of students in a class.
• What is a continuous variable?

  A continuous variable can assume infinitely many values corresponding to a line interval and results from measuring something.
• Provide examples of continuous variables.


  Examples of continuous variables include time, temperature, weight, and height.
• What are the four levels of measurement in statistics?

  1. Nominal
  2. Ordinal
  3. Interval
  4. Ratio
• What is the nominal level of measurement?

  The nominal level is a labeling scheme where numbers serve only as labels or tags for identifying and classifying objects.
• What is an example of nominal data?

  An example of nominal data is the number assigned to a runner in a race.
• What is the ordinal level of measurement?

  The ordinal level is a ranking scale where numbers are assigned to indicate the relative extent to which objects possess some characteristics.
• What can be calculated from ordinal data?

  From ordinal data, we can calculate percentile, quartile, median, and rank-order correlation.
• What is the interval level of measurement?

  The interval level represents equal distances between values, but the location of the zero point is not fixed.
• What is the ratio level of measurement?

  The ratio level possesses all properties of nominal, ordinal, and interval scales, and has an absolute zero point.
• What is data collection?

  • The process of gathering and measuring information on variables of interest.
  • Enables answering research questions, testing hypotheses, and evaluating outcomes.
• What are the two sources of data?

  1. Primary Data
  2. Secondary Data
• What is primary data?

  Primary data is specific information collected by the researcher through surveys, interviews, and experiments.
• Give an example of primary data.

  An example of primary data is the Census of Population and Housing conducted by the Philippines Statistics Authority.
• What is secondary data?


  Secondary data is any material that has been collected from published records and is available from other sources.
• What is an advantage of secondary data?

  Secondary data is economical and saves efforts and expenses.
• What is a disadvantage of secondary data?

  The accuracy of secondary data can be questionable.
• What are some sources of secondary data?

  1. Published reports in newspapers and periodicals
  2. Financial data in annual reports
  3. Records maintained by institutions
  4. Internal reports of government departments
• What are the consequences of improperly collected data?

  • Inability to answer research questions accurately
  • Inability to repeat and validate the study
  • Distorted findings resulting in wasted resources
  • Misleading other researchers
  • Compromising decisions for public policy
  • Causing harm to human participants and animal subjects