Statistics and probability lesson2&3
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This document provides an overview of key concepts in data collection and statistics. It defines important terms like universe, variable, qualitative and quantitative variables. It also distinguishes between discrete and continuous quantitative data. Specifically: - Universe refers to the entire set of units from which data is collected. A variable is any characteristic that can be measured for each unit. - Qualitative variables express categories while quantitative variables answer questions of amount and can be measured. - Discrete data can be counted, while continuous data can be measured to any degree of precision. - Proper data collection requires protecting confidentiality, clarifying questions, and compiling all responses from a target group.
Statistics and probability lesson2&3
- 1. Statistics and Probalility LESSON 2 : DATA COLLECTION ACTIVITY MS. MARIA CHRISTITA POLINAG MIRIAM COLLEGE ADULT EDUCATION
- 2. Important! Facts are collected for purposes of getting aggregate information, but confidentiality should be protected Agencies mandated to collect data is bound by law to protect the confidentiality of information provided by respondents
- 3. Data Collection: provide the needed information to the best of your knowledge before responding to the questionnaire provided it is recommended that each item in the questionnaire should be clarified * Student Information Sheet (SIS)
- 5. Data Collection Census - to compile all your responses and compiling all these records from everyone in the class - data has been gathered from every student in class
- 6. Data - a collection of facts from experiments, observations, sample surveys and censuses, and administrative reporting systems Data Collection
- 7. 3, red, F, 156, 4, 65, 50, 25, 1, M, 9, 40, 68, blue, 78, 168, 69, 3, F, 6, 9, 45, 50, 20, 200, white, 2, pink, 160, 5, 60, 100, 15, 9, 8, 41, 65, black, 68, 165, 59, 7, 6, 35, 45, Data Collection
- 8. Data - facts and figures that are presented, collected and analyzed - either numeric or non-numeric and must be contextualized. Data Collection
- 9. Contextualize data Identify its six W’s or to put meaning on the data 1. Who? Who provided the data? 2. What? What are the information from the respondents and What is the unit of measurement used for each of the information (if there are any)? 3. When? When was the data collected?
- 10. Contextualize data Identify its six W’s or to put meaning on the data 4. Where? Where was the data collected? 5. Why? Why was the data collected? 6. HoW? HoW was the data collected?
- 11. Important! Once the data are contextualized, there is now meaning to the collection of number and symbols
- 12. Statistics and Probalility LESSON 3 : BASIC TERMS IN STATISTICS
- 13. Definition of Basic Terms Universe - the collection or set of units or entities from whom we got the data - collection of respondents from whom one obtain the data
- 14. Definition of Basic Terms Variable - a characteristic that is observable or measurable in every unit of the information asked
- 15. The set of all possible values of a variable is referred to as a population A subgroup of a universe or of a population is a sample In a study there is only one universe but could have several populations. Definition of Basic Terms
- 16. Broad Classification of Variables Qualitative variables express a categorical attribute - do not strictly take on numeric values - answer questions “what kind.” e.g. sex (male or female), religion, marital status, region of residence, highest educational attainment
- 17. Broad Classification of Variables Quantitative (otherwise called numerical) data, whose sizes are meaningful - answer questions such as “how much” or “how many” - have actual units of measure e.g. height, weight, number of registered cars
- 18. Quantitative classification a. Discrete data are those data that can be counted e.g., the number of days for cellphones to fail, the ages of survey respondents measured to the nearest year, and the number of patients in a hospital These data assume only (a finite or infinitely) countable number of values
- 19. Quantitative classification b. Continuous data are those that can be measured e.g. the exact height of a survey respondent and the exact volume of some liquid substance The possible values are uncountably infinite.
- 24. Reference: TEACHING GUIDE FOR SENIOR HIGH SCHOOL - Statistics and Probability by CHED in collaboration with the Philippine Normal University