Bennie D Waller, Longwood University Business Statistics Bennie Waller Longwood University 201 High Street Farmville, 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
Bennie D Waller, Longwood University Measures of Location and Dispersion
Bennie D Waller, Longwood University Measures of Location MEAN MEDIAN MODE # KIDS
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 Deviation Class A Class B Mean77 Range804 Variance9662 Std Dev
Bennie D Waller, Longwood University Empirical Rule Comparison between A & B Mean77 Variance9662 Std Dev
Bennie D Waller, Longwood University Variance
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 End