Bennie D Waller, Longwood University

Business Statistics

Bennie Waller

wallerbd@longwood.edu

434-395-2046Longwood University

201 High StreetFarmville, VA 23901

Bennie D Waller, Longwood University

What is Statistics

Bennie D Waller, Longwood University

Why should you study statistics? Statistics impacts our lives, both personally and professionally everyday.

Examples include the probability that our pizza arrives in 30 minutes or less to the likelihood that a particular toy will be available for Christmas to the probability and extent of the impact of poultry prices due to a bird flu outbreak.

Regardless of one’s concentration, statistics is involved. In the legal profession, medical profession and certainly in business.

You likely already know a great deal about statistics. For example, I bet you know the probability of getting a “Heads” on a single flip of the coin?

Key Issues

Bennie D Waller, Longwood University

Descriptive Statistics – just as the name sounds, it provides a description of the data. According to the US Census, 2013 median household income was $52,250. Last year’s stats class had an average final grade of 82. Both of these are examples of descriptive statistics.

Inferential Statistics – just as its name implies, these statistics provide for an inference to be made based on a particular data set. For example, we could take a sample of 100 students to ascertain the average GPAs of all Longwood students. The larger the sample, the more precise the inference to the larger population.

Key Issues

Bennie D Waller, Longwood University

Key Objectives

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 interest

Bennie D Waller, Longwood University

Qualitative variables – deals with attributes of interest that are non-numeric, e.g., race, hair color, sex

Quantitative variables – deal with numeric data such as income, home prices, temperature

Discrete variables – can only assume certain values. Examples include the number of students in a class or the number of bedrooms.

Continuous variables – can assume any value within a given range, e.g., weight, tire pressure.

Key Issues

Bennie D Waller, Longwood University

Types of data

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Measures of Location and Dispersion

Bennie D Waller, Longwood University

Measures of Location

MEAN

MEDIAN

MODE

# KIDS123345

Bennie D Waller, Longwood University

Understanding Statistics

A B

Bennie D Waller, Longwood University

Measures of Dispersion Most widely used measure of dispersion is variance and standard deviation.

Standard deviation measure the dispersion or volatility around a benchmark (mean or average)

Bennie D Waller, Longwood University

Understanding Statistics

A B

Bennie D Waller, Longwood University

Measures of Dispersion

Bennie D Waller, Longwood University

Empirical Rule

68%

Bennie D Waller, Longwood University

Empirical Rule

95%

Bennie D Waller, Longwood University

Empirical Rule

99.7%

Bennie D Waller, Longwood University

Variance/Standard DeviationClass

AClass

B

95 79

95 75

90 78

90 76

15 77

Mean 77 77

Range 80 4Variance 966 2Std Dev. 31.08 1.41

= = 77

= 966

=

= 2

=

Bennie D Waller, Longwood University

Empirical Rule

Comparison between A & B

Mean 77 77Variance 966 2Std Dev. 31.08 1.41

Bennie D Waller, Longwood University

Variance

0 1000 2000 3000 4000 5000 60000

100000

200000

300000

400000

500000

600000

PRICE

SQFT

PR

ICE

Bennie D Waller, Longwood University

Empirical Rule

Consider an example of Pizza deliveries where the mean is 30 minutes with a standard deviation of 5 minutes. Using your knowledge of the empirical rule, what is the likelihood of a pizza arriving in <30 minutes?

Bennie D Waller, Longwood University

Empirical Rule

Consider an example of Pizza deliveries where the mean is 30 minutes with a standard deviation of 5 minutes. Using your knowledge of the empirical rule, what is the likelihood of a pizza arriving in < 20 minutes

Bennie D Waller, Longwood University

Empirical Rule

Consider an example of Pizza deliveries where the mean is 30 minutes with a standard deviation of 5 minutes. Using your knowledge of the empirical rule, what is the likelihood of a pizza arriving in > 35 minutes

Bennie D Waller, Longwood University

Empirical Rule

Consider an example of Pizza deliveries where the mean is 30 minutes with a standard deviation of 5 minutes. Using your knowledge of the empirical rule, what is the likelihood of a pizza arriving in >20 & <35 minutes?

Bennie D Waller, Longwood University

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