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. - презентация

1 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.

2 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

3 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

4 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

5 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

6 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

7 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

8 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

9 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

10 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

11 Business Statistics Summary of Types of Variables 1-11

12 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

13 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

14 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

15 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

16 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