

There were six terms in the chi-square for this problem - therefore, the number of degrees of freedom is five. Lastly, to determine the significance level we need to know the "degrees of freedom." In the case of the chi-square goodness-of-fit test, the number of degrees of freedom is equal to the number of terms used in calculating chi-square minus one. Using this formula with the values in the table above gives us a value of 13.6. With these sets of figures, we calculate the chi-square statistic as follows: How many of something were expected and how many were observed in some process? In this case, we would expect 10 of each number to have appeared and we observed those values in the left column. The key idea of the chi-square test is a comparison of observed and expected values. The chi-square statistic can be used to estimate the likelihood that the values observed on the blue die occurred by chance. However, it's possible that such differences occurred by chance. There are more 1's and 6's than expected, and fewer than the other numbers. After 60 rolls, the statistician has become convinced that the blue die is loaded.Īt first glance, this table would appear to be strong evidence that the blue die was, indeed, loaded. Unbeknownst to Turner, however, a casino statistician has been quietly watching his rolls and marking down the values of each roll, noting the values of the black and blue dice separately. Crowds are gathering around him to watch his streak - and The Missouri Master is telling anyone within earshot that his good luck is due to the fact that he's using the casino's lucky pair of "bruiser dice," so named because one is black and the other blue. In two hours of playing, he's racked up $30,000 in winnings and is showing no sign of stopping. The Missouri Master) is having a fantastic night at the craps table. One night at the Tunisian Nights Casino, renowned gambler Jeremy Turner (a.k.a.

However, if the die is loaded, then certain numbers will have a greater likelihood of appearing, while others will have a lower likelihood. If the die being used is fair, then the chance of any particular number coming up is the same: 1 in 6. Most dice used in wagering have six sides, with each side having a value of one, two, three, four, five, or six. So how can the goodness-of-fit test be used to examine cheating in gambling? It is easier to describe the process through an example. Since such games usually involve wagering, there is significant incentive for people to try to rig the games and allegations of missing cards, "loaded" dice, and "sticky" roulette wheels are all too common. One of the more interesting goodness-of-fit applications of the chi-square test is to examine issues of fairness and cheating in games of chance, such as cards, dice, and roulette.

To examine hypotheses using such variables, use the chi-square test. There are a number of features of the social world we characterize through categorical variables - religion, political preference, etc. Generally speaking, the chi-square test is a statistical test used to examine differences with categorical variables.
