PreparED Study Materials
STAT 3660: Data Analysis for Biosciences
School: Western Michigan University
Number of Notes and Study Guides Available: 3
Notes
Videos
Poisson Distribution in Event Count & Uranium Discovery
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Explore the dynamics of Poisson distribution using both theoretical understanding and a practical application related to discovering uranium deposits. With the help of Bayes' formula and parameter adjustments, interpret various probabilities and outcomes for event occurrences.
Battery Lifetimes: Mean, Variance & Standard Deviation
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Discover the nuances of analyzing battery lifetime data through mean, variance, and standard deviation computations. Using class boundaries, midpoints, and frequencies, gain insights into the dispersion of battery lifespans and the average deviation from the mean.
Chi-Square Observations: Probability of Exceeding 7.779
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Discover how to compute the likelihood of observations exceeding a certain value in a chi-square distribution with 4 degrees of freedom. Using the binomial distribution formula, evaluate the chances of at most 3 out of 15 observations surpassing the 7.779 mark. Results highlight the intricacies of data distributions.
Analyzing Age Distribution of Proofreaders: A Statistical Approach
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Discover the statistical process behind analyzing the age distribution of proofreaders at a publishing company. Learn how to use the Z-score formula for individual and sample mean probabilities, and how to interpret results using a Z-table.
Two-Sample T-Test: Analyzing Control vs. Supplemented Groups
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Explore the steps to conduct a two-sample t-test using a control and supplemented group. Through hypothesis testing, standard deviation, and P-value interpretation, we analyze the means of both groups to determine statistical differences.
Estimating Study Hours: A 99% Confidence Method"
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Explore how a university dean estimates freshmen study hours using statistical methods. Understand the importance of z-scores, confidence levels, and sample sizes in making accurate predictions. Learn how to ensure results are within a desired error margin.