Engineering Data Analysis Week 1 PDF

WEEK 1 MATH EDA Engineering Data Analysis Engr. Kenth Ramos  ENGINEERING DATA ANALYSIS TOPICS Week 1 Methods of data collection Planning and conducting surveys Planning and conducting experiments: Introduction to design of experiments ...

WEEK 1 MATH EDA Engineering Data Analysis Engr. Kenth Ramos  ENGINEERING DATA ANALYSIS TOPICS Week 1 Methods of data collection Planning and conducting surveys Planning and conducting experiments: Introduction to design of experiments  ENGINEERING DATA ANALYSIS EXPECTED COMPETENCIES Distinguish the different types of data and data collection methods. List and compare the different survey techniques. Determine how to plan and conduct survey. Explain the factors necessary for the design of experiment. ENGINEERING DATA ANALYSIS METHODS OF DATA COLLECTION The task of data collection begins after a research problem has been defined and research design/plan chalked out. ENGINEERING DATA ANALYSIS TYPES OF DATA COLLECTION Primary Secondary Data Data  Primary Data Those which are collected afresh and for the first time, and thus happen to be original in character. ENGINEERING DATA ANALYSIS METHODS OF COLLECTING PRIMARY DATA Observation method Interview method Questionnaires Depth interviews Content Analysis  Observation Method The observation method is the most commonly used method specially in studies relating to behavioural sciences. Under the observation method, the information is sought by way of investigator’s own direct observation without asking from the respondent.  Observation Method Structured Observation The observation is characterised by a careful definition of the units to be observed, the style of recording the observed information, standardised conditions of observation and the selection of pertinent data of observation.  Interview Method The interview method of collecting data involves presentation of oral-verbal stimuli and reply in terms of oral-verbal responses. This sort of interview may be in the form of direct personal investigation or it may be indirect oral investigation.  Interview Method Structured Interview Involve the use of a set of predetermined questions and of highly standardised techniques of recording. The interviewer follows a rigid procedure laid down, asking questions in a form and order prescribed.  Questionnaire In this method a questionnaire is sent to the persons concerned with a request to answer the questions and return the questionnaire. A questionnaire consists of a number of questions printed or typed in a definite order on a form or set of forms. The respondents haveto answer the questions on their own. ENGINEERING DATA ANALYSIS MAIN ASPECTS OF A QUESTIONNAIRE General form Question Sequence Question Formulation and Wording  Questionnaire General Form It can either be structured or unstructured questionnaire. The form of the question may be either closed (i.e., of the type ‘yes’ or ‘no’) or open (i.e., inviting free response) but should be stated in advance and not constructed during questioning.  Questionnaire Question Sequence Proper sequence of questions reduces considerably the chances of individual questions being misunderstood. The question-sequence must be clear and smoothly-moving, meaning thereby that the relation of one question to another should be readily apparent to the respondent, with questions that are easiest to nswer being put in the beginning. Questions should generally be avoided as opening questions in a questionnaire: Questions that put too great a strain on the memory or intellect of the respondent; Questions of a personal character Questions related to personal wealth  Questionnaire Formulating & Wording Should be easily understood Should be simple i.e., should convey only one thought at a time. Should be concrete and should conform as much as possible to the respondent’s way of thinking.  Questionnaire Formulating & Wording “How many razor blades do you use annually?” “How many razor blades did you use last week?”  Secondary Data Those which have already been collected by someone else and which have already been passed through the statistical process. Before using Secondary Data: Reliability of data Suitability of data Adequacy of data ENGINEERING DATA ANALYSIS PLANNING AND CONDUCTING SURVEYS Factors in selecting Method/s Nature, scope and object of enquiry Availability of funds Time factor Precision required ENGINEERING DATA ANALYSIS PRINCIPLES OF SAMPLING  Principles of Sampling Principle 1 – in a majority of cases of sampling there will be a difference between the sample statistics and the true population mean, which is attributable to the selection of the units in the sample.  Principles of Sampling Principle 2 – the greater the sample size, the more accurate the estimate of the true population mean. QUICK ACTIVITY Repeat the discussed procedure with these sample: A = 18, B = 26, C = 32 and D = 40.  Principles of Sampling Principle 3 – the greater the difference in the variable under study in a population for a given sample size, the greater the difference between the sample statistics and the true population mean.  ENGINEERING DATA ANALYSIS BASIC TECHNIQUES OF SAMPLING Random Sampling (SRS) Subjects are selected by random numbers. Systematic Sampling Subjects are selected by using kth number after the first subject is randomly selected from 1 through k. Stratified Sampling Subjects are selected by dividing into groups (strata), and subjects are selected within groups.  ENGINEERING DATA ANALYSIS BASIC TECHNIQUES OF SAMPLING Cluster Sampling Subjects are selected by using an intact group that is representative of the population. ENGINEERING DATA ANALYSIS PLANNING AND CONDUCTING EXPERIMENTS: Introduction to Design Experiments  Internal and External Validity Internal Validity The extent to which the ideas about cause and effect are supported by the study. External Validity The extent to which findings can be generalized to populations or to other settings.  Laboratory and Field Experiments Laboratory Experiments Although there is a sense of artificiality in a natural setting. Laboratory experiments have the advantage of providing a good degree of control over the environment, and of studying the effects on the material or subjects involved.  Laboratory and Field Experiments Field Experiments Subjects are more likely to react and behave normally rather than being affected by artificial conditions. However, the lack of control and ethical issues can raise some problems.  ENGINEERING DATA ANALYSIS TYPES OF EXPERIMENTS True experimental designs Characterized by careful random selection of all the cases to be tested, and the use of a control group parallel to the experimental group, which is used to compare outcomes.  ENGINEERING DATA ANALYSIS TYPES OF EXPERIMENTS Quasi-experimental designs Are used when the random selection of groups cannot be achieved. Pre-experimental designs These designs are used when it is not possible to fulfil the conditions of true experimental designs.  ENGINEERING DATA ANALYSIS TYPES OF EXPERIMENTS Ex post facto The search for the cause of the event, e.g. a plane crash or the outbreak of an unknown disease, relies on the search for, and analysis of, relevant data. ENGINEERING DATA ANALYSIS MANIPULATING MODELS OR SIMULATIONS  Model Models are used to mimic a phenomenon (rather than isolating it as in an experiment) in a form that can be manipulated, to obtain data about the effects of the manipulations.  Diagrammatic Model Diagramming is commonly used to explore a real-life situation in order to investigate what the important variables in the system are and the way in which they influence each other.  Physical Models Three-dimensional representations of an object at a reduced scale.  Mathematical Models/ Simulations Show the effects of different inputs into a system and predict the resultant outcomes.