Statistics in Research Methods (BAFOC 2024D) ver 2.pdf

STATISTICS IN RESEARCH METHODS BAFOC 2024B 16 1300 February 2024  BASIC STATISTICS SAMPLING DESIGN SCOPE OF SAMPLE SIZE DETERMINATION PRESENTATION QUESTIONNAIRE CONSTRUCTIONS DESCRIPTIVE STATISTICS FREQ...

STATISTICS IN RESEARCH METHODS BAFOC 2024B 16 1300 February 2024  BASIC STATISTICS SAMPLING DESIGN SCOPE OF SAMPLE SIZE DETERMINATION PRESENTATION QUESTIONNAIRE CONSTRUCTIONS DESCRIPTIVE STATISTICS FREQUENTLY USED ANALYSIS CREDIBLE CAPABLE SUSTAINABLE  To define statistics and its branches To identify an appropriate sampling design; OBJECTIVES To compute the sample size; To construct questionnaires; To apply descriptive statistics in data analysis; To comment on the analysis commonly used by students. CREDIBLE CAPABLE SUSTAINABLE RECALL: RESEARCH PROCESS CAPABLE CREDIBLE SUSTAINABLE Considerations and steps in formulating a research problem Contents of the research proposal Research Design: Sampling theory and designs; functions and sample size determination Methods of data processing: Use of computers and statistics Disseminate Methods and tools of data and utilize Literature the result collection review Formulating a Constructing an Designing the research Conceptualizing a Selecting a Writing a Collecting Processing the Analyzing Writing a instrument for plan of question and research design sample research the data data the data research report data collection analysis objective proposal Editing of the Field test of the Coding data research tool Principles of scientific writing Developing a Variables and hypotheses: Validity and reliability of the code book definition and typology research tool Operational steps Required theoretical knowledge Figure 1. The research process Required intermediary knowledge 5 CAPABLE CREDIBLE SUSTAINABLE BASIC STATISTICS 6 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Statistics ❑ a science which deals with the: collection, organization, analysis, and interpretation of numerical data. Military Statistics ❑ a science studying both the quantitative and qualitative aspect of military affairs: prior to, during, and after a war. 7 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Two Branches of Statistics 1. Descriptive Statistics 2. Inferential Statistics Descriptive Statistics ❑ summarizes and presents military data in a form of: narrative tables and graphs with summary statistics (e.g., frequency and percentage) ❑ easier to analyze and interpret the data 8 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Frequency counts or absolute number of persons who possess a certain characteristic of interest - e.g., incident cases and prevalent cases Relative frequency (percentage value) proportion (expressed in percentage, %); percentage value number of persons who possess a characteristic of interest over a total number of persons in an observed experiment 9 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Tabular presentation 10 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Inferential Statistics ❑ the process of generalizing or drawing conclusions about the target population on the basis of results obtained from a sample Types of Inferential Statistics 1. Estimation - estimate the true values (unknown parameters) a. point estimation b. interval estimation 2. Hypothesis testing - uses data from a sample to draw conclusions about a population parameter or a population probability distribution 11 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Estimation: a. point estimation e.g., sample mean, sample frequency, sample proportion sample size b. interval estimation e.g., Interquartile Range (1st Quartile – 3rd Quartile) 95% confidence interval (CI) of population mean 90% CI of population proportion Hypothesis Testing: ❑ applied as research hypothesis (in Research paper) ❑ Null hypothesis (Ho) ❑ Alternative hypothesis (Ha) 12  BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Sampling Design To estimate the population parameters: Sampling Population Sample STATISTICAL STATISTIC / PARAMETER MEASURES ESTIMATE MEAN Population Mean (μ) Sample Mean ( x ) PROPORTION Population Proportion (P) Sample Proportion (p) NUMBER OF Computed values: - RESPONDENTS Population Size (N) Sample Size (n) Estimates (SIZE) - sample mean - sample proportion Find out the sample statistics: sample mean, sample proportion Figure 2. Concept of inferential statistics 13 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Example: Sample size 14 BASIC STATISTICS CAPABLE CREDIBLE SUSTAINABLE Examples: Sample proportion 15 CAPABLE CREDIBLE SUSTAINABLE SAMPLING DESIGN 16 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Population ❑ the entire group of individuals or items of interest in the study Target population ❑ the group from which representative information is desired and to which inferences will be made. Sampling population ❑ the population from which a sample will actually be taken 17 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Sample ❑ a part or subset of the population from which the information is collected. Sampling ❑ act of studying or examining only a part of the population to represent the whole. Criteria of Sampling ❑ Representative of the population ❑ Adequate sample size ❑ Practical and feasible ❑ Economy and efficiency 18 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Advantages of Sampling 1. Cheaper 2. Faster 3. Better quality of information 4. More comprehensive data 5. Only possible method for destructive procedures 19 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Two Types of Sampling Design 1. Probability sampling ❑ with determined probability selection of each member of the population ❑ every element of the population has an equal (known) nonzero chance of being selected in the sample. 2. Non-probability sampling ❑ the probability of each member of the population to be selected in the sample is difficult to determine ❑ more practical than probability designs for many clinical research projects ❑ producing a facsimile of a probability sample 20 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Types of Sampling Design Probability Non-probability sampling sampling Simple random Stratified sampling Systematic sampling Cluster sampling Quota sampling Judgmental Accidental Proportionate Stratified sampling Snowball Convenience Disproportionate Consecutive Stratified sampling Figure 3. Types of Sampling Design 21 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Five Methods of Probability Sampling Five Methods of Non-Probability Sampling Design: Designs: 1. Simple Random Sampling 1. Consecutive Sampling 2. Systematic Sampling 2. Judgment or Purposive sampling 3. Stratified Random Sampling 3. Convenience sampling 4. Cluster Sampling 4. Accidental or Haphazard sampling 5. Multi-stage Sampling 5. Quota sampling - Two-stage sampling 6. Snowball sampling e.g., Cluster-Stratified random sampling - Three-stage sampling 22 CAPABLE CREDIBLE SUSTAINABLE PROBABILITY SAMPLING DESIGN 23 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Simple Random Sampling Description: ❑ a method of selecting n units out of the N units in the population in such a way that every element in the population has an equal chance of being included in the sample ❑ may be with replacement or without replacement ❑ randomization techniques: chip-in-the-box method, spin-a-wheel, lottery, the table of random numbers or the running of program number generators in a calculator or computer (e.g., generation of random numbers using MS Excel) 24 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Sampling Population Sample -list of subjects Sample (sampling frame) -subset of population Sampling Estimates of population parameters Find out the sample statistics Figure 4. Simple random sampling 25 SAMPLING DESIGN CAPABLE CREDIBLE SUSTAINABLE Simple Random Sampling: Randomization Techniques ❑ Generating random numbers in MS Excel ❑ by using syntax: =RAND(); then, press enter. ❑ to generate more, highlight the cell where the initial number has been generated, then drag the cursor. ❑ If n