1. Homework Discussion Read pages 446 - 461 Page 467: 17 – 20, 25 – 27, 61, 62, 63, 67 See if you can find an example in your life of a survey that might yield unreliable results

2. The critical issues are: a. Finding a sample that is representative of the population, and b. Determining how big the sample should be. Choosing a good sample of a reasonable size is more important that the sampling rate.

3. Bush's lead gets smaller in poll By Susan Page, USA TODAY WASHINGTON — President Bush leads Sen. John Kerry by 8 percentage points among likely voters, the latest USA TODAY/ CNN/Gallup Poll shows. That is a smaller advantage than the president held in mid- September but shows him maintaining a durable edge in a race that was essentially tied for months. Results based on likely voters are based on the sub sample of 758 survey respondents deemed most likely to vote in the November 2004 General Election. The margin of sampling error is ±4 percentage points.

4. George Gallup explained Whether you poll the Unites States or New York State or Baton Rouge … you need… the same number of interviews or samples. It’s no mystery really – if a cook has two pots of soup on the stove, one far larger than the other, and thoroughly stirs them both, he doesn’t have to take more spoonfuls from one than the other to sample the taste accurately.

5. Statistics is the science of dealing with data. This includes gathering data, organizing data, interpreting data, and understanding data. Descriptive statistics (page 476) is the area which describes large amounts of data in a way that is understandable, useful, and, if need be, convincing.

6. EXAMPLE 1 (page 478). Stat 101 Midterm Exam Scores (25 Points Possible): N=75

7. DESCRIPTIVE STATISTICS A data set is a collection of data values called data points. The size of a data set is the number of data points in it. We use N to represent size.

8. EXAMPLE 1 (page 478). Stat 101 Midterm Exam Scores (25 Points Possible): N=75

9. When possible values of the numerical variable change by minimum increments, the variable is called discrete When the differences between the values of a numerical variable can be arbitrarily small, we call the variable continuous. Baseball stats In statistical usage, a variable is any characteristic that varies with members of a population. (page 481)

10. EXAMPLE 1 (page 478). Stat 101 Midterm Exam Scores (25 Points Possible): N=75

11. TABLE 14-2 Frequency Table for Stat 101 Data Set A frequency table (page 478) is a listing of the scores along with the frequency with which they occur.

12. FrequencyFrequency Score N=75 A bar graph (page 479) is a graph with the possible test scores listed in increasing order on a horizontal axis and the frequency of each test score displayed by the height of the column above that test score. Outliers are data points that do not fit into the overall pattern of the data.

13. Objective 7: Creating structures and systems that model problems and information

14. Instead of representing frequencies a bar graph may represent relative frequencies i.e. the frequencies expressed as percentages of the total population. N=75 Score

15. Fancy bar graphs that use icons instead of bars to show the frequencies, are commonly referred to as pictograms.

16. EXAMPLE 14.3 (page 481). Yearly sales of XYZ Corporation from 1997 through 2002

17. EXAMPLE (page 484). SAT Scores When we have a large number of possible scores we often break up the range of scores into class intervals.

18. EXAMPLE (page 486). Starting Salaries of TSU Graduates When a numerical variable is continuous, its possible values can vary by infinitesimally small increments. Consequently, there are no gaps between the class intervals. In this case we use a variation of a bar graph called a histogram.

19. EXAMPLE (page 486). Starting Salaries of TSU Graduates When a numerical variable is continuous, its possible values can vary by infinitesimally small increments. Consequently, there are no gaps between the class intervals. In this case we use a variation of a bar graph called a histogram.

20. Variables which describe characteristics that cannot be measured numerically are called categorical, or qualitative variables. (page 482) A variable that represents a measurable quantity is called a numerical or quantitative variable.

21. EXAMPLE 3. Enrollment (by School) at Tasmania State University

22. N=15,000 EXAMPLE 3. Enrollment (by School) at Tasmania State University

23. N=15,000 EXAMPLE 3. Enrollment (by School) at Tasmania State University

24. NUMERICAL SUMMARIES OF DATA (page 558) Measures of location (central tendency) are numbers that tell us something about where the values of the data fall. The average of a set of N numbers is obtained by adding the numbers and dividing by N. Example. Average Home runs per season: Mike Sweeney Measures of spread (dispersion) tell us something about how spread out the values of data are.

25. TABLE 14-2 Frequency Table for Stat 101 Data Set

26. FrequencyFrequency Score N=75 Example 9. The Average Test Score in the Stat 101 Test

28. STEP 1. Calculate the total of the data. STEP 2. Calculate N. STEP 3. Calculate the Average. Average = total / N THE AVERAGE (page 559).

29. Homework Read pages 476 – 489 Page 499: 1 – 3, 5, 7 – 11, 19, 21, (for 23, 25, 29, 30, 32, find the mean)