Tiêu đề Math-01-Module-DATA-MANAGEMENT.pdf ✅

Mathematics in Our World | Mathematics as a Tool: Data Management Mathematics in the Modern World 1 Module 3 Mathematics as a Tool: Data Management Contents A. Basic Concepts in Statistics B. Measures of Central Tendency C. Measures of Dispersion D. Measures of Relative Position E. Normal Distribution F. Linear Regression and Correlation Department of Mathematics College of Arts and Sciences Mariano Marcos State University 2019
Mathematics in Our World | Mathematics as a Tool: Data Management Mathematics in the Modern World 2 Introduction Data management is a process by which information is acquired and processed to ensure the accessibility and reliability of the data for its users. One of the most important tool in processing and managing such information is statistics. Statistics is utilized in most areas of human endeavor. It is usually used in education, research, business, agriculture, and other fields and even in everyday life activities. Data or the pieces of information may be collected by conducting a survey, interview, observation, and experiment. The data gathered can be properly organized and presented graphically by a line graph, bar graph or pictograph or with the aid of a statistical table known as frequency distribution table (FDT). A concise and meaningful conclusion is obtained from the analysis and interpretation of data. Relevant information can be deduced from the analysis of numerical descriptions and predictions may be made based on a small group to project the whole population. The work of statistics offers a wide area of concern. Thus, statistics is subdivided into two branches, namely: descriptive statistics and inferential statistics. In descriptive statistics, a set of data is simply described without drawing any inferences or implications. The data is merely summarized and discussed in a clear, concise and informative manner. In inferential statistics, information or inferences concerning a large group known as population is provided based on the study of a representative group or selected members in the population which are identified as sample. Calculating the average rating of a class of 40 students in Math 01 “It is easy to lie with statistics. It is hard to tell the truth without statistics.” Andrejs Dunkel Definition 1: Statistics is a science which deals with the collection, organization, presentation, analysis, and interpretation of data so as to give a more meaningful information. Definition 2: Descriptive statistics refers to the collection, organization, summary, and presentation of data while inferential statistics deals with the interpretation and analysis of data where conclusion is drawn based from the subset of the population.

Mathematics in Our World | Mathematics as a Tool: Data Management Mathematics in the Modern World 4 ii. Qualitative/Categorical variable – describes the quality, category, or character of an element of a population or sample Examples: gender (male or female) hair color (black, brown, blonde) level of satisfaction of a student on his grade (highly satisfied, satisfied, not satisfied) Levels of Measurement A more detailed distinction, termed as the levels of measurement, is used by some researchers in examining the information that is collected. It is classified as follows: 1. Nominal Measurement - numbers or symbols are used to code or classify each element in the population. Note that the assigned numbers have no numerical meaning. Examples: gender, educational background, employment status 2. Ordinal Measurement– uses numerical category that expresses the meaningful order. There is no indication of distance between positions. The numbers become meaningful because they reveal whether one class or category is more or less than the other. Categories are ranked according to the order of their value on the property like first, second, third; oldest, next oldest, youngest. Example: rank in beauty contest 3. Interval Measurement– has equal intervals. There is significance to the distance between any two values. It tells us that one unit differs by a certain amount of the property from another unit. It has no absolute zero. Example: Aptitude test, temperature 4. Ratio Measurement – A variable measured at this level not only includes the concepts of order and interval, but also includes the idea of ’nothingness’, or absolute zero. Example: Measurement of height, weight, ages