Desde

Uses of Statistics

List ways statistics is used.

• Statistics is one of the tools used to make decisions in business

• We apply statistical concepts in our lives

• As a student of business or economics, basic knowledge and skills to organize, analyze, and transform data and to present the information.

Types of Statistics

• Descriptive Statistics - methods oforganizing, summarizing, and presenting data in an informative way.

• Inferential Statistics: a decision, estimate, prediction, or generalization about a population, based on a sample.



Population vs sample



• A population is a collection of all possible individuals, objects, or measurements of interest.

• A sample is a portion, or part, of the population of interestTypes of Statistics

• descriptive Statistics - methods of organizing, summarizing, and presenting data in an informative way.

o EXAMPLE 1: The United States government reports the population of the United States was 179,323,000 in 1960; 203,302,000 in 1970; 226,542,000 in 1980; 248,709,000 in 1990, and 265,000,000 in 2000.

• Inferential statistics: a decision,estimate, prediction, or generalization about a population based on a sample.

• In statistics the word population and sample have a broader meaning. A population or sample may consist of individuals or objects

Population versus Sample

• A population is a collection of all possible individuals, objects, or measurements of interest

• A sample is a portion, or part, of thepopulation of interest.

Types of Variables
• Qualitative or Attribute variable - the characteristic being studied is nonnumeric.
o Examples: Gender, religious affiliation, type of automobile
owned, state of birth, eye color are examples.
• Quantitative variable - information is reported numerically.




o EXAMPLES: balance in your checking account, minutesremaining in class, or number of children in a family.

Quantitative Variables – Classifications

• Discrete variables: can only assume certain values and there are usually “gaps” between values.

o EXAMPLE: the number of bedrooms in a house, or the number of hammers sold at the local Home Depot (1,2,3,...,etc).

• Continuous variable can assume any value within aspecified range.

o EXAMPLE: The pressure in a tire, the weight of a pork chop, or the height of students in a class.

Four Levels of Measurement

• Nominal level - data that is classified into categories and cannot be arranged in any particular order.

o EXAMPLES: eye color, gender, religious affiliation.

o Nominal-Level Data Properties:

oObservations of a qualitative variable 
can only be classified and counted. There is no particular order to the labels.

• Ordinal level – data arranged in some order, but the differences between data values cannot be determined or are meaningless.

o EXAMPLE: During a taste test of 4 soft drinks, Mellow Yellow was ranked number 1, Sprite number 2, Seven-up number 3, and Orange Crush number4.

o Properties:

o Data classifications are represented by sets of labels or names (high, medium, low) that have relative values.

o Because of the relative values, the data classified can be ranked or ordered.

• Interval level - similar to the ordinal level, with the additional property that meaningful amounts of differences between data values can bedetermined. There is no natural zero point.

o EXAMPLE: Temperature on the Fahrenheit scale.

o Properties:

o Data classifications are ordered according to the amount of the characteristic they possess.

o Equal differences in the characteristic are represented by equal differences in the measurements.

• Ratio level - the interval level with an...