rs 10 4.0

• Presentation


  Showcases the data for easy understanding of the readers or future researchers
• Analysis

  The process of breaking up the whole study into its constituent parts of categories according to the specific questions under the SOP
• Interpretation

  Comprehensible statements are made after translating the statistical data
• Discussion of Data


  Results of the investigation are compared and contrasted with those of the reviewed literature and studies
• Classification of data


  • Qualitative (kind)
  • Quantitative
  • Geographical
  • Chronological
• Qualitative data


  Those having the same quality or are of the same kind are grouped together
• Quantitative data


  Data are grouped according to their quantity
• Qualitative data grouping


  • Alphabetically
  • Biggest to smallest class (vice versa)
  • Most to least important
• Quantitative data grouping


  • According to their numerical magnitudes
  • Greatest to smallest (vice versa)
• Geographical data grouping


  • According to geographical location
  • According to direction
• Chronological data grouping


  • Listing down data that occurred first and last those that occurred last (vice versa) according to the purpose of presentation
• Data

  Fact and a supporting detail
• Data Interpretation

  Process of using diverse analytical methods to review data and arrive at relevant conclusions
• Methods of Data Interpretation

  • Direct visual observations of raw data
  • Organized data in tables
  • Graphical representations
  • Numerical/statistical methods
  • Mathematical modeling
• Analysisof Data


  Process of breaking the whole into constituent parts
• Things to Consider in Analyzing Data

  • The highest numerical value
  • The lowest numerical value
  • The most common numerical values
  • The final numerical value
• Discussion of Data


  The flow of discussion of the results is based on how the problems are stated
• Importance of Data Interpretation

  • Informed decision making
  • Identifying trends and anticipating demands
  • Cost efficiency
• Levels of Data Interpretation


  • Level 1: Data collected are compared and contrasted
  • Level 2: Explain the internal validity and consistency/reliability of results
  • Level 3: Explain the external validity and generality/applicability of results
  • Level 4: Relate or connect interpretation to theoretical research or reviewed literature
• Textual Presentation of Data


  Uses statements with numeral or numbers to describe data
• 3 Ways to Present the Data


  • Textual
  • Tabular
  • Graphical
• Tabular Presentation of Data


  A table that helps to represent even a large amount of data in an engaging, easy to read, and coordinated manner
• Major Functional Parts of Statistical Tools

  • Table Number
  • Title
  • Headnote
  • Stub
  • Caption / Column Heading
  • Main Body / Text
  • Source note
  • Footnote
• Graphical Presentation of Data


  A visual display or presentation of data and statistical results
• Types of Graphs


  • Line Graph
  • Bar Graph
  • Circle / Pie Graph
  • Scatter Graph
  • Pictorial Graph
• Line Graph


  Used to show relations between two quantitative variables
• Bar Graph


  Used when the independent variable is categorical
• Circle / Pie Graph


  Used to show percentages and proportions
• Scatter Graph


  Composed of single dots plotted to present the values of single events on the two variables
• Pictorial Graph


  Used to represent simple quantitative differences between groups
• Analysis of Data


  Serves as the basis of the final results of the study
• Interpretation of data


  Process of using diverse analytical methods to review data and arrive at relevant conclusions
• Interpretation of data


  • Helps researchers to categorize
  • Helps researchers to manipulate
  • Helps researchers to summarize
  • The information in order to answer critical questions
• Comprehensible statements


  Made after translating the statistical data
• Sequence of Discussion of Data

  1. Introduction of the table

  2. Analysis of Data

  3. Interpretation of the average or the final statistical results

  4. Discussion of findings

  5. Implications, inferences, & other important info
• Importance of data interpretation


  • Informed decision making
  • Identifying trends and anticipating demands
  • Cost efficiency
• Informed decision making


  Only when a problem is recognized and a goal has been established will the most decisive steps be taken
• Identifying trends and anticipating demands


  • Users may employ data analysis to gain useful insights that they can use to foresee trends
  • When industry trends are detected, they may be used to benefit the whole industry
• Cost efficiency


  The investment will assist you in lowering expenses and increasing the efficiency of your company
• major functional parts of statistical tools

  A) table number

  B) title

  C) head note

  D) caption

  E) body

  F) source

  G) foot note

  H) stubs