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Chapter 01 power point

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Ahmed El-Gendy
Ahmed El-Gendy

This chapter introduces statistics and key concepts. It discusses why statistics is studied, the difference between descriptive and inferential statistics, and the different types of variables - qualitative vs. quantitative, discrete vs. continuous. It also covers levels of measurement - nominal, ordinal, interval, and ratio scales. The goals are to understand why we study statistics and distinguish between these fundamental statistical concepts.

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1-1 Chapter One McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
1-2 Chapter One What is Statistics? GOALS When you have completed this chapter, you will be able to: ONE Understand why we study statistics. TWO Explain what is meant by descriptive statistics and inferential statistics. THREE Distinguish between a qualitative variable and a quantitative variable. FOUR Distinguish between a discrete variable and a continuous variable. FIVE Distinguish among the nominal, ordinal, interval, and ratio levels of measurement. SIX Define the terms mutually exclusive and exhaustive. Goals
1-3 Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions. µ Σ β λ σ What is Meant by Statistics?
1-4 Statistical techniques are used extensively by marketing, accounting, quality control, consumers, professional sports people, hospital administrators, educators, politicians, physicians, and many others. Who Uses Statistics?
1-5 Descriptive Statistics: Methods of organizing, summarizing, and presenting data in an informative way. EXAMPLE 1: A EXAMPLE 2: According Gallup poll found that to Consumer Reports, 49% of the people in a General Electric washing survey knew the name machine owners reported of the first book of the 9 problems per 100 Bible. The statistic 49 machines during 2001. describes the number The statistic 9 describes out of every 100 the number of problems persons who knew the out of every 100 machines. answer. Types of Statistics
1-6 Inferential Statistics: A decision, estimate, prediction, or generalization about a population, based on a sample. A Population A Sample is a is a Collection portion, or part, of all possible of the population individuals, of interest objects, or measurements of interest. Types of Statistics
1-7 Example 1: TV Example 2: Wine networks constantly tasters sip a few drops monitor the of wine to make a popularity of their decision with respect programs by hiring to all the wine waiting Nielsen and other to be released for sale. organizations to sample the Example 3: The accounting preferences of TV department of a large firm will viewers. select a sample of the invoices to check for accuracy for all the invoices of the company. #1 Types of Statistics (examples of inferential statistics)
1-8 For a Qualitative or Attribute Variable the characteristic being studied is nonnumeric. G en der E ye C o lo r S ta te of T ype of car B irt h Types of Variables
1-9 In a Quantitative Variable information is reported numerically. Balance in your checking account Minutes remaining in class Number of children in a family Types of Variables
1-10 Quantitative variables can be classified as either Discrete or Continuous. Discrete Variables: can only assume certain values and there are usually “gaps” between values. Example: the number of bedrooms in a house, or the number of hammers sold at the local Home Depot (1,2,3,…,etc). Types of Variables
1-11 A Continuous Variable can assume any value within a specified range. The pressure in a tire The weight of a pork chop The height of students in a class. Types of Variables
1-12 D ATA Q u a lit a t iv e o r a t t r ib u t e Q u a n t i t a t i v e o r n u m e r ic a l (ty p e o f c a r o w n e d ) d is c r e t e c o n t in u o u s ( n u m b e r o f c h ild r e n ) ( t im e t a k e n fo r a n e x a m ) Summary of Types of Variables
1-13 There are four levels of data Nominal Ordinal Interval Ratio Levels of Measurement
1-14 Nominal level G en der Data that is classified into categories and cannot be arranged E ye in any particular C o lo r order. Nominal data
1-15 Nominal level variables must be: Mutually exclusive An individual, object, or measurement is included in only one category. Exhaustive Each individual, object, or measurement must appear in one of the categories. Levels of Measurement
1-16 Ordinal level: involves data arranged in some order, but the differences between data values cannot be determined or are meaningless. During a taste test of 4 soft drinks, 4 2 Coca Cola was ranked number 1, Dr. Pepper number 3 2, Pepsi number 3, 1 and Root Beer number 4. Levels of Measurement
1-17 Interval level Similar to the ordinal level, with the additional property that meaningful amounts of differences between data values can be determined. There is no natural zero point. Temperature on the Fahrenheit scale. Levels of Measurement
1-18 Ratio level: the interval level with an inherent zero starting point. Differences and ratios are meaningful for this level of measurement. M ile s t ra v e le d b y s a le s M o n t h ly in c o m e re p re s e n t a t iv e in a m o n t h o f su rg eo n s Levels of Measurement

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Chapter 01 power point

  • 1. 1-1 Chapter One McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
  • 2. 1-2 Chapter One What is Statistics? GOALS When you have completed this chapter, you will be able to: ONE Understand why we study statistics. TWO Explain what is meant by descriptive statistics and inferential statistics. THREE Distinguish between a qualitative variable and a quantitative variable. FOUR Distinguish between a discrete variable and a continuous variable. FIVE Distinguish among the nominal, ordinal, interval, and ratio levels of measurement. SIX Define the terms mutually exclusive and exhaustive. Goals
  • 3. 1-3 Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions. µ Σ β λ σ What is Meant by Statistics?
  • 4. 1-4 Statistical techniques are used extensively by marketing, accounting, quality control, consumers, professional sports people, hospital administrators, educators, politicians, physicians, and many others. Who Uses Statistics?
  • 5. 1-5 Descriptive Statistics: Methods of organizing, summarizing, and presenting data in an informative way. EXAMPLE 1: A EXAMPLE 2: According Gallup poll found that to Consumer Reports, 49% of the people in a General Electric washing survey knew the name machine owners reported of the first book of the 9 problems per 100 Bible. The statistic 49 machines during 2001. describes the number The statistic 9 describes out of every 100 the number of problems persons who knew the out of every 100 machines. answer. Types of Statistics
  • 6. 1-6 Inferential Statistics: A decision, estimate, prediction, or generalization about a population, based on a sample. A Population A Sample is a is a Collection portion, or part, of all possible of the population individuals, of interest objects, or measurements of interest. Types of Statistics
  • 7. 1-7 Example 1: TV Example 2: Wine networks constantly tasters sip a few drops monitor the of wine to make a popularity of their decision with respect programs by hiring to all the wine waiting Nielsen and other to be released for sale. organizations to sample the Example 3: The accounting preferences of TV department of a large firm will viewers. select a sample of the invoices to check for accuracy for all the invoices of the company. #1 Types of Statistics (examples of inferential statistics)
  • 8. 1-8 For a Qualitative or Attribute Variable the characteristic being studied is nonnumeric. G en der E ye C o lo r S ta te of T ype of car B irt h Types of Variables
  • 9. 1-9 In a Quantitative Variable information is reported numerically. Balance in your checking account Minutes remaining in class Number of children in a family Types of Variables
  • 10. 1-10 Quantitative variables can be classified as either Discrete or Continuous. Discrete Variables: can only assume certain values and there are usually “gaps” between values. Example: the number of bedrooms in a house, or the number of hammers sold at the local Home Depot (1,2,3,…,etc). Types of Variables
  • 11. 1-11 A Continuous Variable can assume any value within a specified range. The pressure in a tire The weight of a pork chop The height of students in a class. Types of Variables
  • 12. 1-12 D ATA Q u a lit a t iv e o r a t t r ib u t e Q u a n t i t a t i v e o r n u m e r ic a l (ty p e o f c a r o w n e d ) d is c r e t e c o n t in u o u s ( n u m b e r o f c h ild r e n ) ( t im e t a k e n fo r a n e x a m ) Summary of Types of Variables
  • 13. 1-13 There are four levels of data Nominal Ordinal Interval Ratio Levels of Measurement
  • 14. 1-14 Nominal level G en der Data that is classified into categories and cannot be arranged E ye in any particular C o lo r order. Nominal data
  • 15. 1-15 Nominal level variables must be: Mutually exclusive An individual, object, or measurement is included in only one category. Exhaustive Each individual, object, or measurement must appear in one of the categories. Levels of Measurement
  • 16. 1-16 Ordinal level: involves data arranged in some order, but the differences between data values cannot be determined or are meaningless. During a taste test of 4 soft drinks, 4 2 Coca Cola was ranked number 1, Dr. Pepper number 3 2, Pepsi number 3, 1 and Root Beer number 4. Levels of Measurement
  • 17. 1-17 Interval level Similar to the ordinal level, with the additional property that meaningful amounts of differences between data values can be determined. There is no natural zero point. Temperature on the Fahrenheit scale. Levels of Measurement
  • 18. 1-18 Ratio level: the interval level with an inherent zero starting point. Differences and ratios are meaningful for this level of measurement. M ile s t ra v e le d b y s a le s M o n t h ly in c o m e re p re s e n t a t iv e in a m o n t h o f su rg eo n s Levels of Measurement