ENM317 EngineeringStatisticsCourse 1:Introduction

PROF. DR. NİHAL ERGİNEL

Books

Probability and Statistics in Engineeringand Management Science,

W. Hines

D.C. Montgomery

Wiley Publication

Course organization

1. Definations

2. Data description and definitions

3. Random sample and sampling distributions

4. Point and Interval estimations

5. Statistical hypothesis testing

6. Nonparametric hypothesis testing

Grades1. Midterm (%20)

2. Midterm (%20)

One quiz (%10)

One homework (%10)

Final (%40)

DefinitionsStatistics

A collection of methods for planningexperiments, obtaining data, and thenorginizing, summarizing, presenting, analyzing, interpreting, and drawingconclusions based on the data

Data

Observations ( such as measurements, survey responses) that have been collected andrecorded.

DefinitionsPopulation

The complete collection of all elements (scores, people, measurements, and so on) to be studied. The collection is complete in the sense that it includes all subjects to be studied.

DefinitionsSample data must be collected in an apropriate way such as through a process of random selection.

Sample

A sub-collection or sub-set of population

DefinitionsParameter

A numerical measurement describing somecharacteristic of a population

DefinitionsQualitative data (categorical orattribute data)

Representing numbers or countabledata

Example: the number of defectiveunits

Discrete data

Quantitative data

representing measurement values

Example: the weights of packedbiscuits

Continuous data

Collecting Engineering Data

Retrospective data

Observational study

Designed experiment

DefinitionsRandom sample

Member of population are selectedin such a way that each individualmember has an equal chance of being selected

Simple Random sample (sample size n)

Subjects selected in such a way everyposible sample of the same sample size n has the same chance of being chosen

DefinitionsSampling

Selecting n units (sample size n) from population and then estimate thapopulation parameters from sample

Why we need the sampling do not reach to the population

reaching to the population can be costly

reaching to the population can take more time

measurement technique may be destructive and sample can’t use again

Methods of SamplingSimple Random sample (sample size n)

Subjects selected in such a way every posible sample of the same sample size n has the same chance of being chosen

Systematic sampling

Select same starting point and then select every k th element in thepopulation

Convenience sampling

Use result that are easy to get

Methods of SamplingStratified sampling

Subdivide the population into at least two different subgroups that share thesame characteristics, then draw a sample from each subgroups (stratum)

Cluster sampling

Dive the population into sections (or clusters), then randomly select samplefrom each clusters

DefinitionsSampling error

The difference between a sample result and the true population result, suchan error results from chance sample fluctuations

The End