Parent GuideChapter 13 builds on the statistical ideas of Chapter 2 and the probability ideas of Chapter 12 to show how to make predictions. Inferential statisticsMaking predictions about a large group from a smaller group is called inferential statistics. One of the most familiar examples of inferential statistics is polling; it?s impossible to survey everyone, so only a sample is polled and the results are generalized to the whole group, or population. The validity of the generalization depends on how well the smaller sample represents the population. One way to get a representative sample is by using a random process. After choosing a sample randomly, someone trying to describe the full population must describe the sample, using statistics studied in Chapter 2. These include measures of central tendency, such as mean and median, and measures of spread, such as standard deviation. They also include a new idea: the shape of the data?generally, the degree to which the data are symmetric to the mean. The third step in making predictions about the population is to decide how confident you are that the sample statistics match the corresponding numbers in the population. Polling results are often reported as being ?accurate to within 4 points.? To make decisions about what it means to be ?accurate? and what interval is associated with that degree of accuracy, your student will think about what would happen if many random samples were taken. Bivariate statisticsSometimes you want to make predictions about one characteristic of a population based on another characteristic. For example, you might want to predict the height of an oak tree based on its circumference. Here, students collect data about two characteristics and find ways of describing their correlation?either through a correlation coefficient or graphs. Summary problemFrom the sample census data on age and income, what can you conclude about the population? Age and Income Age (yr)  Income ($)  31  6000  43  0  48  35,000  5  0  41  60,000  37  65,970  21  20  50  3000  35  68,400  48  22,330  10  0  74  36,636  32  44,000  54  8500  54  27,000  42  50,125  16  600  45  31,300  38  34,500  77  18,000  46  63,058  2  0  67  65,568  33  50,592  54  80,000 
  Age (yr)  Income ($)  16  0  14  0  44  106,000  8  0  56  36,868  42  20,000  39  6500  61  35,000  19  750  22  2400  40  17,000  27  10,090  22  15,000  38  72,000  39  51,000  30  0  36  1500  4  0  22  1561  37  52,523  23  6000  40  15,462  31  24,634  3  0  42  87,500 

Questions you might ask in your role as student to your student:  What is the population from which this sample was taken?
 What do you think the mean age of the population is?
 What?s a 95% confidence interval for that age?
 How confident can you be that the mean income of the population is $19,000?
 How well do age and income correlate?
Sample answers 