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- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/05%3A_Continuous_Random_Variables/5.05%3A_Chapter_ReviewThis page offers an overview of continuous probability density functions (pdfs) and cumulative distribution functions (cdf). It highlights that pdfs represent probabilities for continuous random varia...This page offers an overview of continuous probability density functions (pdfs) and cumulative distribution functions (cdf). It highlights that pdfs represent probabilities for continuous random variables, with total area equaling one. The text covers uniform and exponential distributions, explaining their definitions, key statistical measures (mean and standard deviation), and their probability density functions.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/05%3A_Continuous_Random_Variables/5.06%3A_Formula_ReviewThis page covers properties of continuous probability density functions (pdf) and cumulative distribution functions (cdf), focusing on uniform and exponential distributions. It details their character...This page covers properties of continuous probability density functions (pdf) and cumulative distribution functions (cdf), focusing on uniform and exponential distributions. It details their characteristics, including mean, standard deviation, and probability calculations. The page also introduces the Poisson distribution and its probability calculation formula based on the mean.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/11%3A_The_Chi-Square_Distribution/11.09%3A_Formula_ReviewThis page provides an overview of the chi-square distribution, detailing its definition, expected mean, and standard deviation. It explains the testing of a single variance, along with its formula and...This page provides an overview of the chi-square distribution, detailing its definition, expected mean, and standard deviation. It explains the testing of a single variance, along with its formula and the procedure that includes calculating degrees of freedom. It also covers the goodness-of-fit test, the test of independence, and the test for homogeneity, each with their formulas and degrees of freedom.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/11%3A_The_Chi-Square_Distribution/11.08%3A_Chapter_ReviewThis page discusses the importance of the chi-square distribution in evaluating data fit, population distribution equality, event independence, and variability. It highlights the role of degrees of fr...This page discusses the importance of the chi-square distribution in evaluating data fit, population distribution equality, event independence, and variability. It highlights the role of degrees of freedom in shaping the distribution, which is right-skewed and approaches normality for df > 90.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/06%3A_The_Normal_Distribution/6.03%3A_Estimating_the_Binomial_with_the_Normal_DistributionThis page discusses estimating binomial processes using various probability distributions, particularly the normal, Poisson, and hypergeometric distributions. It notes that the normal distribution eff...This page discusses estimating binomial processes using various probability distributions, particularly the normal, Poisson, and hypergeometric distributions. It notes that the normal distribution effectively approximates binomial outcomes when both np and n(1-p) exceed five. An example involving Australian Shepherd puppies illustrates these calculations for binomial probabilities, highlighting the utility of the normal distribution in simplifying computations.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/11%3A_The_Chi-Square_Distribution/11.02%3A_Test_of_a_Single_VarianceThis page emphasizes the importance of understanding both the mean and variability in populations, especially in production and assessments. It covers hypothesis testing for population variance, detai...This page emphasizes the importance of understanding both the mean and variability in populations, especially in production and assessments. It covers hypothesis testing for population variance, detailing null and alternative hypotheses, test statistics, and examples of variance testing in various contexts like education and service quality.
- https://stats.libretexts.org/Bookshelves/Applied_Statistics/Business_Statistics_(OpenStax)/11%3A_The_Chi-Square_DistributionThis page offers a comprehensive overview of the Chi-Square Distribution, covering its characteristics and applications in hypothesis testing, including variance, goodness-of-fit, independence, and ho...This page offers a comprehensive overview of the Chi-Square Distribution, covering its characteristics and applications in hypothesis testing, including variance, goodness-of-fit, independence, and homogeneity tests. It highlights the Goodness-of-Fit test's role in evaluating data alignment with specific distributions and includes review exercises and references for further study.
