Business Statistics 1-1 Chapter One What is Statistics? GOALS When you have completed this chapter, you will be able to: ONE Define what is meant by 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.

Business Statistics What is Meant by Statistics? Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions. 1-2

Business Statistics Who Uses Statistics? Statistical techniques are used extensively by marketing, accounting, quality control, consumers, professional sports people, hospital administrators, educators, politicians, physicians, etc

Business Statistics Types of Statistics Descriptive Statistics: Methods of organizing, summarizing, and presenting data in an informative way. EXAMPLE 1: A Gallup poll found that 49% of the people in a survey knew the name of the first book of the Bible. The statistic 49 describes the number out of every 100 persons who knew the answer. EXAMPLE 2: According to Consumer Reports, Whirlpool washing machine owners reported 9 problems per 100 machines during The statistic 9 describes the number of problems out of every 100 machines. 1-4

Business Statistics Types of Statistics Inferential Statistics: A decision, estimate, prediction, or generalization about a population, based on a sample. A population is a collection of possible individuals, objects, or measurements of interest. A sample is a portion, or part, of the population of interest. 1-5

Business Statistics Types of Statistics (examples of inferential statistics) EXAMPLE 1: TV networks constantly monitor the popularity of their programs by hiring Nielsen and other organizations to sample the preferences of TV viewers. EXAMPLE 2: The accounting department of a large firm will select a sample of the invoices to check for accuracy for all the invoices of the company. EXAMPLE 3: Wine tasters sip a few drops of wine to make a decision with respect to all the wine waiting to be released for sale. 1-6

Business Statistics Types of Variables Qualitative or attribute variable: the characteristic or variable being studied is nonnumeric. EXAMPLES: Gender, religious affiliation, type of automobile owned, state of birth, eye color. 1-7

Business Statistics Types of Variables Quantitative variable: the variable can be reported numerically. EXAMPLE: balance in your checking account, minutes remaining in class, number of children in a family. 1-8

Business Statistics Types of Variables 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. (1,2,3,..., etc...). 1-9

Business Statistics Types of Variables Quantitative Variables can be classified as either discrete or continuous. Continuous variables: can assume any value within a specific range. EXAMPLE: The time it takes to fly from Toledo to New York. 1-10

Business Statistics Summary of Types of Variables 1-11

Business Statistics Levels of Measurement Nominal level (scaled): Data that can only be classified into categories and cannot be arranged in an ordering scheme. EXAMPLES: eye color, gender, religious affiliation. 1-12

Business Statistics Levels of Measurement (nominal level) Mutually exclusive: An individual or item that, by virtue of being included in one category, must be excluded from any other category. EXAMPLE: eye color. Exhaustive: each person, object, or item must be classified in at least one category. EXAMPLE: religious affiliation. 1-13

Business Statistics Levels of Measurement Ordinal level: involves data that may be arranged in some order, but differences between data values cannot be determined or are meaningless. EXAMPLE: During a taste test of 4 colas, cola C was ranked number 1, cola B was ranked number 2, cola A was ranked number 3, and cola D was ranked number

Business Statistics Levels of Measurement 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. EXAMPLE: Temperature on the Fahrenheit scale. 1-15

Business Statistics Levels of Measurement Ratio level: the interval level with an inherent zero starting point. Differences and ratios are meaningful for this level of measurement. EXAMPLES: money, heights of NBA players. 1-16