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If the p-value is less than the significance level, then the null hypothesis is rejected. The p-value is the probability of obtaining a Chi Square Value as extreme or more extreme than the observed value, assuming the null hypothesis is true. The p-value can also be calculated from the Chi Square Value and the degrees of freedom. The null hypothesis is that there is no significant difference between the observed frequency and the expected frequency. If the Chi Square Value is greater than the Critical Value, then the null hypothesis is rejected. The Critical Value can be found in a Chi Square Distribution Table. The degrees of freedom is the number of categories minus one. It depends on the level of significance and the degrees of freedom.
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The Critical Value is the value that is used to determine whether the Chi Square Value is significant or not. The difference between the observed and expected frequency is squared, divided by the expected frequency, and then summed across all categories. To calculate the Chi Square Test Statistic, the observed frequency for each category is compared to the expected frequency for that category. The test is based on the Chi Square Distribution, which is a probability distribution that describes the distribution of the sum of squared standard normal deviates. It is used to analyze data in which variables are classified into categories. The Chi Square Test is a statistical test used to determine if there is a significant difference between the observed frequency and the expected frequency of categorical data. The distribution is often used to model the behavior of random variables that are the sum of the squares of other random variables. The Chi Square Distribution is a continuous distribution, meaning that it can take on any value within a certain range. The distribution is characterized by a single parameter, known as the degrees of freedom, which determines the shape of the distribution. The distribution is named after the Greek letter chi (χ), which is used to represent the distribution. It is often used in statistical analysis to determine whether a sample is representative of a larger population, or to test the hypothesis that two samples are drawn from the same population. The Chi Square Distribution is a probability distribution that is used to determine the likelihood of observing a certain set of values in a sample.
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A chi square distribution calculator is a tool that helps to calculate the probability of the chi square distribution, making it easier to analyze and interpret statistical data. The distribution is characterized by its degrees of freedom, which is the number of independent variables in the data set. It is commonly used in statistics to analyze data and determine if there is a relationship between two variables. The chi square distribution is a probability distribution that is used to test the independence of two variables. The calculator takes in the degrees of freedom and the level of significance to calculate the probability of the chi square distribution. This type of distribution is commonly used in statistics to test the independence of two variables. A chi square distribution calculator is a tool that is used to calculate the probability of a chi square distribution.