1. ISTANBUL STOCK EXCHANGE (BIST) FELL 6 POINTS IN AVERAGE TODAY THE UNITED STATES DOLLAR (USD) APPRECIATED BY 4 PERCENT LAST WEEK AGAINST TURKISH LIRA (TRL). AT THE 95% CONFIDENCE LEVEL, IT IS ESTIMATED THAT THE EXCHANGE RATE WILL BE BETWEEN _____ AND ____. THE LATEST SURVEY INDICATES THAT THE PRESIDENT`S APPROVAL RATING NOW STANDS AT 60 PERCENT

2. THE PRICE OF KOC HOLDING STOCK WILL BE HIGHER IN SIX MONTH THAN IT IS NOW THE PRICE OF KOC HOLDING STOCK IS LIKELY TO BE HIGHER IN SIX MONTH THAN IT IS NOW

3. THE STAGES FOR STATISTICAL THINKING ARE: 1- DEFINE THE PROBLEM 2- DETERMINE WHAT DATA IS NEEDED 3- SELECT A SAMPLE 4- COLLECT DATA 5- SUMMARIZE AND ANALYZE DATA 6- MAKE INFERENCES AND DECISIONS BASED ON INFORMATION

4. The Journey to Making Decisions Begin Here: Identify the Problem DATA INFORMATION KNOWLEDGE DECISION MAKING Descriptive Statistics, Probability, Computers Experience, Theory, Literature Inferential Statistics, Computers

5. DATA: Specific observations of measured numbers. INFORMATION: Processed and summarized data yielding facts and ideas. KNOWLEDGE: Selected and organized information that provides understanding, recommendations, and the basis for decisions.

6. Descriptive Statistics include graphical and numerical procedures that summarize and process data and are used to transform data into information Descriptive Statistics include graphical and numerical procedures that summarize and process data and are used to transform data into information Inferential Statistics provide the bases for predictions, forecasts, and estimates that are to transform information to knowledge Descriptive Statistics include graphical and numerical procedures that summarize and process data and are used to transform data into information Descriptive Statistics include graphical and numerical procedures that summarize and process data and are used to transform data into information

7. POPULATION: A complete set of individuals, objects or measurements having common observable characteristics. Examples of Populations - Names of all registered voters in TURKEY - Incomes of all families living in ANKARA - Annual return of all stocks traded on the ISTANBUL STOCK EXCHANGE - Grade Point Averages of all the students in your University - BILKENT

8. SAMPLE: A subset or part of a population Examples of Samples - Names of 50.000 registered voters in TURKEY - Incomes of 10.000 families living in ANKARA - Annual return of 150 stocks traded on the ISTANBUL STOCK EXCHANGE - Grade Point Averages of 500 students from different departments in your University - BILKENT

9. Example: Imagine that a public opinion polling firm has been contracted to conduct a study concerning the percentage of the state`s registered voters who approve of nuclear power as an energy source. As part of the polling process, 750 individuals are randomly selected from the voter registration list and carefully interviewed. Elements? Random Sample ? Variable of Interest? Data? Statistic? Population?

11. Below Average Below Average Above Average Above Average Average Average Above Average Above Average Average Average Above Average Above Average Average Average Above Average Above Average Below Average Below Average Poor Poor Excellent Excellent Above Average Above Average Average Average Above Average Above Average Below Average Below Average Poor Poor Above Average Above Average Average Average Frequency Distribution n Example: Marada Inn

12. Sample of Parts Cost($) for 50 Tune-ups Frequency Distribution n Example: Hudson Auto Repair

13. Dot Plot 5060708090100110 50 60 70 80 90 100 110 Cost ($) Tune-up Parts Cost n Example: Hudson Auto Repair

14. Stem-and-Leaf Display 5 6 7 8 9 10 2 7 2 2 2 2 5 6 7 8 8 8 9 9 9 1 1 2 2 3 4 4 5 5 5 6 7 8 9 9 9 0 0 2 3 5 8 9 1 3 7 7 7 8 9 1 4 5 5 9 a stem a leaf Example: Hudson Auto Repair Example: Hudson Auto Repair

15. Note: Data is in ascending order.

16. Measures of Location n Mean n Median n Mode n Percentiles n Quartiles n Weighted Mean

17. Sample Mean Number of observations in the sample Number of observations in the sample Sum of the values of the n observations Sum of the values of the n observations

18. Population Mean  Number of observations in the population Number of observations in the population Sum of the values of the N observations Sum of the values of the N observations

19. Weighted Mean Denominator: sum of the weightsDenominator: weights Numerator: sum of the weighted data values Numerator: sum of the weighted data values If data is from a population,  r eplaces x. If data is from a population,  r eplaces x. where: x i = value of observation i x i = value of observation i w i = weight for observation i w i = weight for observation i

20. Weighted Mean Example: Construction Wages Example: Construction Wages Ron Butler, a custom home builder, is looking over the Expenses he incurred for a house he just completed constructing. For the purpose of pricing future projects, he would like to know the average wage ($/hour) he paid the workers he employed. (The cost of materials is estimated in advance by the architect.) Listed below are the categories of worker he employed, along with their respective wage and total hours worked. Ron Butler, a home builder, is looking over the expenses he incurred for a house he just built. For the purpose of pricing future projects, he would like to know the average wage ($/hour) he paid the workers he employed. Listed below are the categories of worker he employed, along with their respective wage and total hours worked. Ron Butler, a home builder, is looking over the expenses he incurred for a house he just built. For the purpose of pricing future projects, he would like to know the average wage ($/hour) he paid the workers he employed. Listed below are the categories of worker he employed, along with their respective wage and total hours worked.

21. Weighted Mean Example: Construction Wages Example: Construction Wages FYI, equally-weighted (simple) mean = $21.21 FYI, equally-weighted (simple) mean = $21.21

22. 80 th Percentile i = ( p /100) n = (80/100)70 = 56 Averaging the 56 th and 57 th data values: 80th Percentile = (635 + 649)/2 = 642 Note: Data is in ascending order. Example: Apartment Rents Example: Apartment Rents

23. 80 th Percentile “At least 80% of the items take on a items take on a value of 642 or less.” value of 642 or less.” “At least 20% of the items take on a value of 642 or more.” value of 642 or more.” 56/70 =.8 or 80%14/70 =.2 or 20% Example: Apartment Rents Example: Apartment Rents

24. Quartiles Quartiles are specific percentiles. Quartiles are specific percentiles. First Quartile = 25th Percentile First Quartile = 25th Percentile Second Quartile = 50th Percentile = Median Second Quartile = 50th Percentile = Median Third Quartile = 75th Percentile Third Quartile = 75th Percentile

25. A wholesaler sold 575, 410 and 520 microwave ovens at prices (in USD) 75, 125 and 100 respectively. What is the mean price of the ovens sold?

26. Example: The following data represent the duration (in days) of Space Shuttle voyages for the years 1992-1994. (18 values) 8,9,9,14,8,8,10,7,6,9,7,8,10,14,11,8,14,11 Q: Find The Mode

27. MONTHLY STARTING SALARY (In TRL) GraduateMonthly Starting Salary 12,850 22,950 33,050 42,880 52,755 62,710 72,890 83,130 92,940 103,325 112,920 122,880 TOTAL: 35,280