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Hope someone knows and can explain a little bit!

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- Thread starter Mårten
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In summary, the conversation discusses the use of different distributions to test for statistical significance in an opinion poll. The normal distribution can be used for a difference of means test, while the binomial distribution is suitable for a discrete variable with multiple possible values. However, for a large enough sample size, the binomial distribution can be approximated with a normal distribution. This is due to the central limit theorem, which allows for simpler analysis.

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Hope someone knows and can explain a little bit!

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- #3

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I know that when doing repeated measurements of for instance the length of 20-year old girls in a population, I will get a normal distribution. But now we don't have a continuous variable (length), but instead a discrete variable with seven possible values (the seven different partys). Doesn't that make any difference?

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- #5

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Ah, okey. That seems reasonable. I think I understand now. Thank you!

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mXSCNT said:

Ah, central limit theorem, how we love thee.

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Okey, I see.

A probability distribution for political parties is a mathematical representation of the likelihood of each party winning in an election. It takes into account various factors such as past voting patterns, demographics, and current events to predict the probability of each party's success.

A probability distribution for political parties is calculated using statistical methods and data analysis. Different models and techniques may be used, such as regression analysis or machine learning algorithms, to determine the probabilities of each party's success in an election.

A probability distribution provides valuable insights for political parties to make strategic decisions and allocate resources effectively. It can help parties understand their chances of winning an election and identify key areas to focus on to improve their chances of success.

While a probability distribution can provide a good estimate of the likelihood of each party winning an election, it is not a guarantee of the actual outcome. Many other factors, such as unforeseen events or changes in public opinion, can influence the final result.

A probability distribution can be used to analyze political trends by tracking changes in party probabilities over time. This can help identify shifts in public opinion and predict potential outcomes in future elections. It can also highlight the impact of certain events or policies on party probabilities.

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