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CHAPTER 1: OBTAINING DATA VARIABLE - Is a measure or characteristic or property of a STATISTICS population or sample that may have a number - Science that deals with the collection,...

CHAPTER 1: OBTAINING DATA VARIABLE - Is a measure or characteristic or property of a STATISTICS population or sample that may have a number - Science that deals with the collection, of different values. organization, presentation, analysis, and interpretation of data. COLLECTION OF DATA - first step in conducting statistical inquiry. DESCRIPTIVE STATISTICS - It seeks merely to describe data. DATA GATHERING - Organize and summarize describe - A systematic method of collecting and quantitative data. measuring data from different sources of information to provide answers to relevant INFERENTIAL STATISTICS questions. - deals with making a judgment or a conclusion about a population INVESTIGATOR - A person who conducts the inquiry. POPULATION/UNIVERSE - Refers to the totality of objects, persons, PRIMARY DATA places, things used in a particular study. - Data collected in the process of investigation SAMPLE SECONDARY DATA - Is any subset of population or few members - Are those already in existence for some other of a population. purpose than answering the question in hand DATA THREE BASIC METHODS OF DATA - facts, figures and information collected on GATHERING some characteristics of population or sample. - Can be quali or quanti 1. RETROSPECTIVE STUDY - Uses the population or sample of the UNGROUPED / RAW DATA historical data which had been archived over a - Data that are not organized in any specific period of time. way. Simply a collection of data as they are - identifies interesting phenomena but gathered difficulty of obtaining solid and reliable explanation is encountered GROUPED DATA - raw data organized into groups or categories 2. OBSERVATIONAL STUDY with corresponding frequencies (data id - Process or population is observed and referred to as frequency distribution) disturbed as little as possible. PARAMETER 3. DESIGN EXPERIMENT - Is the descriptive measure of a characteristic - Deliberate or purposeful changes in the of a population controllable variables of the system or process is done. Are needed to establish a cause-and- STATISTIC effect relationship. - measure of a characteristic of sample. CONSTANT - Is a characteristic or property of a population which is common to all members of the group. SURVEY STRATIFIED SAMPLING - Is a method of asking respondents some well- - May often be factors which divide up the constructed questions. population into sub-population and the - An efficient way of collecting information measurement of interest may vary among the and easy to administer wherein a variety of different sub-populations. (PROCESS) information is collected STRATIFIED SAMPLE SELF-ADMINISTERED SURVEYS - Is obtained by taking samples from each - Are less expensive than interviews. Can be stratum or sub-group of a population. administered in large numbers and does not (RESULT) require many interviews and there is less pressure on respondents. STRATIFIED SAMPLING TECHNIQUES - lower response rate than in personal -Are generally used, when the population is interviews. heterogenous, or dissimilar, where certain homogenous, or similar, sub-populations can NON-PROBABILITY SAMPLING be isolated. - is also called judgment or subjective sampling. SIMPLE RANDOM SAMPLING - is convenient and economical but the - Is the most appropriate when the entire inferences made based on the findings are not population from which the sample is taken is so reliable. homogenous. CONVENIENCE SAMPLING CLUSTER SAMPLING - Uses a device in obtaining information from - is a sampling technique where the entire the respondents which favors the researcher population is divided into groups or clusters, but can cause bias to the respondents. and a random sample of these clusters are selected. PURPOSIVE SAMPLING - the selection of respondents is predetermined EXPERIMENTS according to the characteristic of interest made - series of tests conducted in a systematic by the researcher. manner to increase understanding of an existing process or to explore new product or TWO TYPES OF QUOTA SAMPLING: process. PROPORTIONAL - Major characteristics of the population by DESIGN OF EXPERIMENT (DOE) sampling a proportional amount of each is -is a tool to develop an experimentation represented. strategy that maximizes learning using minimum resources. NON-PROPORTIONAL QUOTA - is widely and extensively used by engineers SAMPLING and scientists in improving existing process - Every member of the population is given an increase yield and decrease in variability equal chance to be selected as a part of the - a technique needed to identify the “vital few” sample. factors in the most efficient manner. SIMPLE RANDOM SAMPLING METHODOLOGY OF DOE - is the basic random sampling technique -ensures that all factors and their interactions where a group of subjects is selected for study are systematically investigated. from s larger group. FIVE STAGES IN DESIGN OF SIMPLE EVENT EXPERIMENTS - an event with one outcome 1. PLANNING COMPOUND EVENT - Identification of the objectives of conducting -an event with more than one outcome the experiment or investigation, assessment of time and available resources to achieve the SAMPLE SPACE objectives. - Is the set of all possible outcomes or results of a random experiment. 2. SCREENING -represented by the letter S. - are used to identify the important factors that affect the process under investigation out of NULL SPACE the large pool of potential factors. - is a subset of the sample space that contains no elements and is denoted by the symbol null. SCREENING EXPERIMENTS -also called an empty space - Are usually efficient designs which require few executions and focused on the vital MUTUALLY EXCLUSIVE EVENTS factors and not on interactions - they have no elements in common 3. OPTIMIZATION DEPENDENT - Determines the best setting of the factors to -two outcomes are said to be dependent if achieve the objectives of the investigation. knowing that one of the outcomes has occurred (adjustments) affects the probability of the other 4. ROBUSTNESS TESTING CONDITIONAL PROBABILITY - make the product or process insensitive to - An event B in a relationship to an event A is variations resulting from changes in factors the probability that event B occurs after event that affect the process that are beyond the A has already occurred. P(B|A). control of the analyst CHAPTER 3: DISCRETE PROBABILITY 5. VERIFICATION DISTRIBUTION - involves the validation of the optimum settings by conducting a few follow up DISCRETE PROBABILITY experimental runs. (finalization) DISTRIBUTION - describe the probability of occurrence of each CHAPTER 2: PROBABILITY value of a random variable. PROBABILITY DISCRETE RANDOM VARAIBLE - is simply how likely an event is to happen. - is a random variable that has countable values, such as list of non-negative integers EXPERIMENT - is used to describe any process that generates RANDOM VARIABLES a set of data. - Is a variable whose value is subject to variations due to chance. EVENT - does not have a single fixed value. - consists of a set of possible outcomes of a probability experiment. Can be on or more DISCRETE RANDOM VARIABLES outcome. - can take on either a finite or at most a countably infinite set of discrete value. AYAW KO NA SUNDAN SUKO NA AKO -YOUSUF