Assist. Prof. Dr. Mohammed Al-dujaili
Department of Ceramics Engineering and Building Materials
Faculty of Materials Engineering
University of Babylon
2016-2017
Lecture 1
Stage: Second
Subject: Engineering Statistics
Introduction to Engineering Statistics
Definitions
Concept of Statistics
Collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions.
Engineering statistics
Engineering statistics combines engineering and statistics
1. Design of Experiments (DOE) is a methodology for formulating scientific and engineering problems using statistical models.
2. Quality control and process control use statistics as a tool to manage conformance to specifications of manufacturing processes and their products.
3. Time and methods engineering use statistics to study repetitive operations in manufacturing in order to set standards and find optimum (in some sense) manufacturing procedure.
4. Reliability engineering which measures the ability of a system to perform for its intended function (and time) and has tools for improving performance.
5. Probabilistic design involving the use of probability in product and system design.
6. System identification uses statistical methods to build mathematical models of dynamical systems from measured data. System identification also includes the optimal design of experiments for efficiently generating informative data for fitting such models. Figure below is showing the conceptual model of engineering statistic.
Figure: Conceptual model of engineering statistic
Variable
Characteristic or attribute that can assume different values
Random Variable
A variable whose values are determined by chance. As explained in Figure below.
Figure: Random Variable
Population
All subjects possessing a common characteristic that is being studied.
Sample
A subgroup or subset of the population.
Parameter
Characteristic or measure obtained from a population.
Statistic (not to be confused with Statistics)
Characteristic or measure obtained from a sample.
Descriptive Statistics
Collection, organization, summarization, and presentation of data.
Inferential Statistics
Generalizing from samples to populations using probabilities. Performing hypothesis testing, determining relationships between variables, and making predictions.
Figure: Inferential Statistics
Qualitative Variables
Variables which assume non-numerical values. Quantitative Variables: Variables which assume numerical values.
Discrete Variables
Variables which assume a finite or countable number of possible values. Usually obtained by counting.
Continuous Variables
Variables which assume an infinite number of possible values. Usually obtained by measurement.
Nominal Level
Level of measurement which classifies data into mutually exclusive, all inclusive categories in which no order or ranking can be imposed on the data.
Ordinal Level
Level of measurement which classifies data into categories that can be ranked. Differences between the ranks do not exist.
Interval Level
Level of measurement which classifies data that can be ranked and differences are meaningful. However, there is no meaningful zero, so ratios are meaningless.
Ratio Level
Level of measurement which classifies data that can be ranked, differences are meaningful, and there is a true zero. True ratios exist between the different units of measure.
Random Sampling
Sampling in which the data is collected using chance methods or random numbers.
Systematic Sampling
Sampling in which data is obtained by selecting every k the object.
Convenience Sampling
Sampling in which data is which is readily available is used.
Stratified Sampling
Sampling in which the population is divided into groups (called strata) according to some characteristic. Each of these strata is then sampled using one of the other sampling techniques.
Cluster Sampling
Sampling in which the population is divided into groups (usually geographically). Some of these groups are randomly selected, and then all of the elements in those groups are selected.
Levels of Measurement
There are four levels of measurement: Nominal, Ordinal, Interval, and Ratio. These go from lowest level to highest level. Data is classified according to the highest level which it fits. Each additional level adds something the previous level didn t have.
• Nominal is the lowest level. Only names are meaningful here.
• Ordinal adds an order to the names.
• Interval adds meaningful differences
• Ratio adds a zero so that ratios are meaningful.
المادة المعروضة اعلاه هي مدخل الى المحاضرة المرفوعة بواسطة استاذ(ة) المادة . وقد تبدو لك غير متكاملة . حيث يضع استاذ المادة في بعض الاحيان فقط الجزء الاول من المحاضرة من اجل الاطلاع على ما ستقوم بتحميله لاحقا . في نظام التعليم الالكتروني نوفر هذه الخدمة لكي نبقيك على اطلاع حول محتوى الملف الذي ستقوم بتحميله .
الرجوع الى لوحة التحكم
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