Fraud.org was created by the National Consumers League (NCL) to combat the growing problem of telemarketing and Internet fraud by improving prevention and enforcement. NCL works to protect and promote social and economic justice for consumers and workers int he United States and abroad.

You work for NCL as a statistical analyst. You are studying data on fraud. Part of your analysis involves testing the goodness of fit, testing for independence, comparing variances, and performing ANOVA.

1) Goodness of Fit

The table at the right shows an expected distribution of the ages of fraud victims. The table also shows the results of a survey of 1000 randomly selected fraud victims. Using alpha = 0.01, perform a chi-square goodness-of-fit test. What can you conclude?

Expected Survey Age distribution results Under 18 0.44% OO 18-25 12.66% 128 26-35 16.31% 155 36-45 16.98% 171 46-55 21.26% 220 56-65 17.82% 164 Over 65 14.52% 154 TABLE FOR EXERCISE 1Type of Age Fraud Under 20 20-29 30-39 40-49 50-59 60-69 60-79 80+ Total Sweepstakes 10 60 70 130 90 160 280 200 1000 Credit cards 20 180 260 240 180 70 30 20 1000 Total 30 240 330 370 270 230 310 220 2000