1. © 2012 McGraw-Hill Ryerson Limited1 © 2009 McGraw-Hill Ryerson Limited

2. © 2012 McGraw-Hill Ryerson Limited2 Lind Marchal Wathen Waite

3. © 2012 McGraw-Hill Ryerson Limited3 Explain why we study statistics. Explain what is meant by descriptive statistics and inferential statistics. Distinguish between a qualitative variable and a quantitative variable. Describe how a discrete variable is different from a continuous variable. Distinguish among the nominal, ordinal, interval, and ratio levels of measurement. Learning Objectives LO 1 2 3 4 5

4. © 2012 McGraw-Hill Ryerson Limited4 Why Study Statistics? LO 1

5. © 2012 McGraw-Hill Ryerson Limited5 Three main reasons: 1.Data are everywhere. 2.Statistical techniques are used to make many decisions that affect our lives. 3.No matter what your career, you will make decisions that involve data. An understanding of statistical methods will help you make these decisions more effectively. Why Study Statistics? LO 1

6. © 2012 McGraw-Hill Ryerson Limited6 Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions. What Is Meant By Statistics? LO 1

7. © 2012 McGraw-Hill Ryerson Limited7 Types of Statistics LO 2

8. © 2012 McGraw-Hill Ryerson Limited8 Descriptive Statistics Methods of organizing, summarizing, and presenting data in an informative way. 1.Frequency distributions 2.Chart forms 3.Central tendency 4.Measures 5.Data clustering Types of Statistics LO 2

9. © 2012 McGraw-Hill Ryerson Limited9 Inferential Statistics The methods used to determine something about a population, based on a sample: 1.A population is the entire set of individuals or objects of interest or the measurements obtained from all individuals or objects of interest. 2.A sample is a portion, or part, of the population of interest. Types of Statistics LO 2

10. © 2012 McGraw-Hill Ryerson Limited10 1.Prohibitive cost of surveying the whole population 2.Destructive nature of some tests 3.Physical impossibility of capturing the population Types of Statistics LO 2

11. © 2012 McGraw-Hill Ryerson Limited11 Descriptive Statistics: 1.Population census data 2.Weekly earnings of hospitality workers 3.Individual responses of registered voters regarding their choice of Prime Minister of Canada Inferential Statistics: 1.46% of high school students can solve fractions, decimals, and percentages. 2.77% of high school students can correctly total a restaurant menu. Types of Statistics LO 2

12. © 2012 McGraw-Hill Ryerson Limited12 You Try It Out! LO 2 The Wooden Furniture Company asked a sample of 2564 consumers to try out a newly developed living room set in a showroom. Of the 2564 sampled, 2126 said they would purchase the furniture if it were marketed. a)What should the Wooden Furniture Company report to its Board of Directors regarding the percentage of acceptance of the living room set? b)Is this an example of descriptive statistics or inferential statistics? Explain.

13. © 2012 McGraw-Hill Ryerson Limited13 Types of Variables LO 3

14. © 2012 McGraw-Hill Ryerson Limited14 Types of Variables Qualitative The characteristic being studied is non-numeric. Examples: Gender, religious affiliation, type of automobile owned, country of birth, eye colour Quantitative Information is reported numerically. Examples: The balance in your chequing account, the ages of company CEOs, the life of a battery, the number of children in a family LO 3

15. © 2012 McGraw-Hill Ryerson Limited15 A Discrete Variable is Different from a Continuous Variable LO 4

16. © 2012 McGraw-Hill Ryerson Limited16 Quantitative Variables: Classifications Discrete Variables Can only assume certain values and there are usually “gaps” between values Examples: Number of bedrooms in a house, number of cars arriving at a shopping centre, number of students in a statistics course section Continuous Variables Can assume any value within a specified range Examples: Tire pressure, weight of shipment of grain, amount of cereal in a box, duration of a flight LO 4

17. © 2012 McGraw-Hill Ryerson Limited17 Summary of the Variable Types Types of Variables LO 3

18. © 2012 McGraw-Hill Ryerson Limited18 Mutually Exclusive a property of a set of categories such that an individual or object is included in only one category Exhaustive a property of a set of categories such that each individual or object must appear in at least one category Important Properties LO 3

19. © 2012 McGraw-Hill Ryerson Limited19 Level of Measurement LO 5

20. © 2012 McGraw-Hill Ryerson Limited20 Levels of Measurement Nominal The variable of interest is divided into mutually exclusive categories or outcomes. There is no natural order to the outcomes. Examples: colour of M&Ms, gender Ordinal Data classifications are represented by labels or names (high, medium, low) that are mutually exclusive. Data classifications are ranked or ordered according to the particular trait they possess. Examples: professor ratings, terrorist attack risk levels LO 5

21. © 2012 McGraw-Hill Ryerson Limited21 Levels of Measurement LO 5 Interval Data classifications are mutually exclusive and exhaustive. Data classifications are ordered according to the amount of the characteristic they possess. Equal differences in the characteristic are represented by equal differences in the measurement. Examples: temperature, shoe size, IQ scores

22. © 2012 McGraw-Hill Ryerson Limited22 Levels of Measurement LO 5 Ratio Data classifications are mutually exclusive and exhaustive. Data classifications are ordered according to the amount of the characteristics they possess. Equal differences in the characteristic are represented by equal differences in the numbers assigned to the classifications. The zero point is the absence of the characteristic and the ratio between two numbers is meaningful. Examples: wages, weight, height

23. © 2012 McGraw-Hill Ryerson Limited23 Levels of Measurement: Summary of Major Characteristics LO 5 Levels of Data

24. © 2012 McGraw-Hill Ryerson Limited24 You Try It Out! LO 5 What level of measurement is reflected in the following data? a)A sample number of books read in a year by 50 readers is given below: b)In a survey of 300 television viewers, 100 were from a low income group, 150 from a middle income group, and 50 from a high income group. 1543111731714 1066 18134171611 513816945181612 71191411125 1713 812 621613159

25. © 2012 McGraw-Hill Ryerson Limited25 “There are three kinds of lies: lies, damn lies, and statistics”. -- Benjamin Disraeli “Figures don’t lie: liars figure”. Statistics can be misused and data can be presented in misleading ways. Ethics and Statistics LO 5

26. © 2012 McGraw-Hill Ryerson Limited26 can provide accurate information in seconds reduce the likelihood of an error include options such as Excel, Excel add-ins (such as Megastat), or MINITAB Computer Applications LO 5

27. © 2012 McGraw-Hill Ryerson Limited27 I.Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions. IIThere are two types of statistics. ADescriptive statistics are procedures used to organize and summarize data. Chapter Summary

28. © 2012 McGraw-Hill Ryerson Limited28 BInferential statistics involve taking a sample from a population and making estimates about a population based on the sample results. 1.A population is an entire set of individuals or objects of interest or the measurements obtained from all individuals or objects of interest. 2.A sample is a part of the population. Chapter Summary

29. © 2012 McGraw-Hill Ryerson Limited29 IIIThere are two types of variables. A.A qualitative variable is categorical or nonnumeric. 1.Usually we are interested in the number or percent of the observations in each category. 2.Qualitative data are usually summarized in graphs and bar charts. Chapter Summary

30. © 2012 McGraw-Hill Ryerson Limited30 B.There are two types of quantitative variables and they are usually reported numerically. 1.Discrete variables can assume only certain values, and there are usually gaps between values. 2.A continuous variable can assume any value within a specified range. Chapter Summary

31. © 2012 McGraw-Hill Ryerson Limited31 IVThere are four levels of measurement. A.With the nominal level, the data are sorted into categories with no particular order to the categories. B.The ordinal level of measurement presumes that one classification is ranked higher than another. C.The interval level of measurement has the ranking characteristic of the ordinal level of measurement plus the characteristic that the distance between values is a constant size. Chapter Summary

32. © 2012 McGraw-Hill Ryerson Limited32 D.The ratio level of measurement has all the characteristics of the interval level, plus there is a meaningful zero point and the ratio of two values is meaningful. Chapter Summary