1. 1 Economics 240A Power One

2. 2 Outline w Course Organization w Course Overview w Resources for Studying

4. Organization ( Cont.)

5. 5 Course Overview w Topics in Statistics Descriptive Statistics Exploratory Data Analysis Probability and Distributions Proportions Interval Estimation Hypothesis Testing Correlation and Regression Analysis of Variance

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10. 10 Resources for Studying w Keller & Warrack Text Readings CDROM PowerPoint Slide Shows Appletns w Instructor Lecture Notes Lab Notes & Exercises Problem Sets PowerPoint Slide Shows

11. 11 http://econ.ucsb.edu

12. 12 Keller & Warrack CDROM

13. 13 http://www.duxbury.com/statistics

14. 14 Student Book Companion Siten

15. 15 Keller & Warrack Slide Show w Excerpts from Ch. 2

16. 16 Graphical Descriptive Techniques Chapter 2

17. 17 2.1 Introduction w Descriptive statistics involves the arrangement, summary, and presentation of data, to enable meaningful interpretation, and to support decision making. w Descriptive statistics methods make use of graphical techniques numerical descriptive measures. w The methods presented apply to both the entire population the population sample

18. 18 2.2Types of data and information w A variable - a characteristic of population or sample that is of interest for us. Cereal choice Capital expenditure The waiting time for medical services w Data - the actual values of variables Interval data are numerical observations Nominal data are categorical observations Ordinal data are ordered categorical observations

19. 19 Types of data - examples Interval data Age - income 5575000 4268000.. Age - income 5575000 4268000.. Weight gain +10 +5. Weight gain +10 +5. Nominal Person Marital status 1married 2single 3single.. Person Marital status 1married 2single 3single.. Computer Brand 1IBM 2Dell 3IBM.. Computer Brand 1IBM 2Dell 3IBM..

20. 20 Types of data - examples Interval data Age - income 5575000 4268000.. Age - income 5575000 4268000.. Nominal data With nominal data, all we can do is, calculate the proportion of data that falls into each category. IBM Dell Compaq OtherTotal 25 11 8 6 5 0 50% 22% 16% 12% IBM Dell Compaq OtherTotal 25 11 8 6 5 0 50% 22% 16% 12% Weight gain +10 +5. Weight gain +10 +5.

21. 21 Types of data – analysis  Knowing the type of data is necessary to properly select the technique to be used when analyzing data.  Type of analysis allowed for each type of data Interval data – arithmetic calculations Nominal data – counting the number of observation in each category Ordinal data - computations based on an ordering process

22. 22 Cross-Sectional/Time-Series Data w Cross sectional data is collected at a certain point in time Marketing survey (observe preferences by gender, age) Test score in a statistics course Starting salaries of an MBA program graduates w Time series data is collected over successive points in time Weekly closing price of gold Amount of crude oil imported monthly

23. 23 2.3 Graphical Techniques for Interval Data w Example 2.1: Providing information concerning the monthly bills of new subscribers in the first month after signing on with a telephone company. Example 2.1 Collect data Prepare a frequency distribution Draw a histogram

24. 24 Largest observation Collect data (There are 200 data points Prepare a frequency distribution How many classes to use? Number of observations Number of classes Less then 505-7 50 - 2007-9 200 - 5009-10 500 - 1,00010-11 1,000 – 5,00011-13 5,000- 50,00013-17 More than 50,00017-20 Class width = [Range] / [# of classes] [119.63 - 0] / [8] = 14.95 15 Largest observation Largest observation Smallest observation Smallest observation Smallest observation Smallest observation Largest observation Example 2.1Example 2.1: Providing information

25. 25 Draw a Histogram Example 2.1Example 2.1: Providing information

26. 26 nnnn 0 20 40 60 80 153045607590 105120 Bills Frequency What information can we extract from this histogram About half of all the bills are small 71+37=108 13+9+10=32 A few bills are in the middle range Relatively, large number of large bills 18+28+14=60 Example 2.1Example 2.1: Providing information

27. 27 w It is generally best to use equal class width, but sometimes unequal class width are called for. w Unequal class width is used when the frequency associated with some classes is too low. Then, several classes are combined together to form a wider and “more populated” class. It is possible to form an open ended class at the higher end or lower end of the histogram. Class width

28. 28 w There are four typical shape characteristics Shapes of histograms

29. 29 Positively skewed Negatively skewed Shapes of histograms

30. 30 A modal class is the one with the largest number of observations. A unimodal histogram The modal class Modal classes

31. 31 Descriptive Statistics w Central Tendency mode median mean w Dispersion standard deviation interquartile range (IQR)

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34. 34 Exploratory Data Analysis w Stem and Leaf Diagrams w Box and Whiskers Plots

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