In politics, marketing, etc we often want to estimate a percentage or proportion p. One calculation in statistical polling is the margin of error- the largest (reasonable) error that the poll can have. For example, a poll result of 72% with a margin of error of 4% indicates that p is most likely between 68% and 76% In a made up poll, the proportion of people who like dark chocolate more than milk chocolate was 39% with a margin of error of 2.2%. Describe the conclusion about p using an absolute value equality. I came up with .368 <= p <= .412 but I don't think it's right, please show steps so I can see where I went wrong
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
In politics, marketing, etc we often want to estimate a percentage or proportion p. One calculation in statistical polling is the margin of error- the largest (reasonable) error that the poll can have. For example, a poll result of 72% with a margin of error of 4% indicates that p is most likely between 68% and 76%
In a made up poll, the proportion of people who like dark chocolate more than milk chocolate was 39% with a margin of error of 2.2%. Describe the conclusion about p using an absolute value equality.
I came up with .368 <= p <= .412 but I don't think it's right, please show steps so I can see where I went wrong!
Solution:
Given information;
Sample proportion of people who like dark chocolate more than milk chocolate
E= 0.022 Margin of error
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