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Euchre One of the authors and some statistician friends have an ongoing series of Euchre games that will stop when one of the two teams is deemed to be statistically significantly better than the other team. Euchre is a card game and each game results in a win for one team and a loss for the other. Only two teams are competing in this series, which we'll call team A and team B. (a) Define the parameter(s) of interest. (b) What are the null and alternative hypotheses if the goal is to determine if either team is statistically significantly better than the other at winning Euchre? (c) What sample statistic(s) would they need to measure as the games go on? (d) Could the winner be determined after one or two games? Why or why not? (e) Which significance level, \(5 \%\) or \(1 \%,\) will make the game last longer?

Short Answer

Expert verified
The parameter is the success proportions of teams A and B. The null hypothesis is that the teams have an equal chance of winning (\(p_A = p_B\)), and the alternative hypothesis is that the chances are not equal (\(p_A \neq p_B\)). The winning proportions of each team should be measured as games go on. A winner could not be determined after one or two games due to insufficient sample size. Using a 1% significance level would make the game series last longer than a 5% significance level due to the need for stronger evidence to reject the null hypothesis.

Step by step solution

01

Defining the Parameter

Here, the parameter of interest is the true success proportions for teams A and B, with success being defined as winning a game of Euchre. Denote \(p_A\) as the probability of team A winning, and \(p_B\) for team B
02

Formulating the Hypotheses

The null hypothesis (\(H_0\)) would be that both teams have an equal chance of winning the game, that is \(p_A = p_B\). The alternative hypothesis (\(H_A\)) is that the teams do not have an equal chance of winning, hence \(p_A \neq p_B\)
03

Sample Statistics Measurement

As games proceed, they would need to measure the proportion of games won by each team, which will serve as estimates for \(p_A\) and \(p_B\)
04

Number of Games for Winner Determination

The number of games required would be dependent on the difference in team performance. If the difference in proportions is large, fewer games would be required to conclude whether there is a statistically significant difference. However, deciding a winner after one or two games would likely not provide enough evidence to reject the null hypothesis due to a lack of sufficient sample size. So, the winner could not be decided after one or two games.
05

Deciding Significance Level

A lower significance level makes a hypothesis test more conservative and requires more evidence to reject the null hypothesis. Therefore, choosing a significance level of 1% would make the game series last longer than if a 5% significance level was chosen.

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