QMM 280

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# QMM 280 - PowerPoint PPT Presentation

QMM 280. Introduction to Statistics. Dr. Barry A. Wray Associate Professor Department of IS and OM. Introduction. What is a definition for statistics?

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### QMM 280

Introduction to Statistics

Dr. Barry A. Wray

Associate Professor

Department of IS and OM

Introduction
• What is a definition for statistics?
• The field of Statistics is concerned with the collection, presentation, and analysis of data in order to assist a manager in the decisions making process.
• What is the “story” of the data?
Two Main Branches of Statistics

Descriptive

Inferential

Infer or make conclusions from an analysis of the data

• Describe the data
• Central Tendency
• Dispersion
• Distribution
Sources of Data
• Survey Data
• Historical Records
• Published Data
• Manufacturing Data
• Sales Data
TYPES OF DATA
• QUALITATIVE
• Data which is non numerical
• QUANTITATIVE (Continuous)
• Data which is numerical in nature
QUALITATIVE
• NOMINAL
• Data classified into categories with no order implied
• What color are your eyes?
• Accountant
• Economist
• Manager
• Teacher
• Unemployed (Student)
• ORDINAL
• Categorical data with ordering implied
• How was the movie last night?
• Excellent
• Very Good
• Good
• Fair
• Poor
QUANTITATIVE (Continuous)
• Discrete
• Usually integer values
• Number of people
• Number of defective items
• Continuous
• Fractional values
• Weight
• Age
• Height
• Time
Types of Data
• Time Series Data is data collected through time.
• Stock prices are an example of time series data. Tomorrow’s starting price for a stock depends on the ending price of that stock today. Stock prices “move” over time so it is important to factor in this effect.
• Cross Sectional Data does not have a “time” component
• Data collected on a variable at a single point in time. For example you might be interested in doing a study of comparative housing prices for the 8 major cities in June 2000.
Examining the Data
• First step in any analysis is to examine the data
• Arrays
• Listing the data in ascending or descending order.
• Useful in identifying common or outlying values
• Tables
• Summarizing the data into categories
• Useful for visualizing important characteristics of the data
• Frequency Distributions
• Graphical Representations
• Pie and Bar Charts
• Histograms
Descriptive Measures
• Central Tendency
• Mean
• Median
• Mode
• Dispersion
• Range
• Mean Absolute Deviation
• Standard Deviation
Statistical Terminology
• Population – the collection of ALL entities possessing some characteristic we are interested in.
• Sample – some subset of a Population
• Population Parameter – a summary measure of some characteristic we are interested in for all entities in a population.
• sample statistic – a summary measure computed from a sample and used to estimate a Parameter from the Population where the sample was derived from.
Selecting a sample
• Why sample?
• Population size - Census too cumbersome
• Destructive sampling
simple random sampling (srs)
• Definition
• Each member of the population has an equally likely chance of being selected.
• sampling with replacement
• Basis of most statistical inference
Errors in Collecting Data
• sampling error
• Error caused because no sample is exactly representative of population
• Chance differences that occur when a sample is selected
• Non sampling error
• Error caused by human.

Population Parameters are computed from a census of the entire Population and are used to describe some characteristic about the Population you are interested in (X).

Population

µx

Parameters

sx

Population Parameters are computed from a census of the entire Population and are used to describe some characteristic about the Population you are interested in (X).

Population

µx

Parameters

sx

A sample is a subset of a larger Population

sample

sx

sample statistics are computed from sample data and used to estimate Population Parameters

statistics