2. Econ 3790: Business and Economics Statistics Instructor: Yogesh Uppal Email: yuppal@ysu.edu

3. Chapter 1 Goals of the course Data and statistics

4. Why use Statistics? To make sense of large amounts of data: What are the demographics of Youngstown in 2000? Have U.S. wages increased since 1975? To test hypotheses: Is demand curve downward sloping? Are GDP and Saving Rate positively correlated? To make predictions: What might happen to savings behavior after a large tax cut?

5. Data: Basic Definitions Data: a set of measurements Dataset: all data collected for one study Element, or unit: an entity on which data are collected Variable: a property or attribute of each unit Observation: the values of all variables for one unit

6. Data: Basic Definitions Stock Annual Earn/ Stock Annual Earn/ Exchange Sales($M) Share($) Company Dataram Dataram EnergySouth EnergySouth Keystone Keystone LandCare LandCare Psychemedics Psychemedics AMEX 73.10 0.86 AMEX 73.10 0.86 OTC 74.00 1.67 OTC 74.00 1.67 NYSE365.70 0.86 NYSE365.70 0.86 NYSE111.40 0.33 NYSE111.40 0.33 AMEX 17.60 0.13 AMEX 17.60 0.13 Variables Element Names Names Data Set Observation

7. Data: Scales of Measurement Four scales of measurement: Nominal, ordinal, interval, and ratio scales Scale determines which methods of summarization and analysis are appropriate for any given variable

8. Data: Scales of Measurement Characteristic Nominal, like a label or name for a characteristic e.g., color: red, green, blue race: black, Hispanic, white, Asian binary: (male, female), (yes, no), (0, 1) Ordinal, still a characteristic, but having a natural order e.g., how was service?: poor, average, good

9. Data: Scales of Measurement Numeric Interval scale Numeric data showing the properties of ordinal data e.g., SAT scores, Fahrenheit temperature Ratio scale Ordered, numeric data with real zero e.g., income, distance, price, quantity http://www.math.sfu.ca/~cschwarz/Stat- 301/Handouts/node5.html

10. Data: Other Classifications Qualitative, or categorical: measures a quality Quantitative: numeric values that indicate how much or how many Cross-sectional: data collected at one point in time Time series: data collected over several time periods Panel or longitudinal: combination of cross- sectional and time series

11. Data: Summary of Definitions QualitativeQualitativeQuantitativeQuantitative NumericalNumerical NumericalNumerical NonnumericalNonnumerical DataData NominalNominalOrdinalOrdinalNominalNominalOrdinalOrdinalIntervalIntervalRatioRatio

12. Statistical Inference: Definitions Population: the set of all elements of interest in a study Sample: a subset of the population Statistical Inference: the process of using data obtained from a sample to make estimates and test hypotheses about the characteristics of a population

13. Statistical Inference: Process 1. Population consists of all tune-ups. Average cost of parts is unknown unknown. 2. A sample of 50 engine tune-ups is examined. 3. The sample data provide a sample average parts cost of $79 per tune-up. 4. The sample average is used to estimate the population average. population average.

14. Descriptive Statistics: Definition Descriptive statistics are the tabular, graphical, and numerical methods used to summarize data

15. Descriptive Statistics: Common Methods Some common methods: Tabular Frequency table (for one variable) Crosstabulation, or crosstab (for more than one variable) Graphical Bar graph (for categorical variables) Histogram (for interval- or ratio-scaled variables) Scatterplot (for two variables) Numerical Mean (arithmetic average)