Applied Statistics and Probability for Engineers: Montgomery

إحصاء ونظريات احتمالات متقدمة
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Udemy
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العربية
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Other Teaching & Academi
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Applied Statistics and Probability for Engineers: Montgomery
8
students
15.5 hours
content
Mar 2025
last update
$99.99
regular price

Why take this course?

🌟 Advanced Statistics and Probability Theories by Mohamed Sayed El-Ashhab 🌟

Course Description:

Dive deep into the world of Advanced Statistics and Probability Theories with our comprehensive online course. This course is meticulously designed to equip you with a robust understanding of estimating population parameters, mastering the normal distribution, and leveraging various statistical methods to make informed decisions in engineering and scientific contexts.

What You Will Learn:

  • Parameter Estimation:

    • Understand the general concepts of estimating population or probability distribution parameters.
    • Appreciate the significance of the normal distribution as a sampling distribution and grasp the Central Limit Theorem.
    • Learn about important properties of point estimators, including bias, variance, and mean square error.
  • Constructing Point Estimators:

    • Master the method of moments and the method of maximum likelihood to construct point estimators.
    • Comprehend how to compute the precision of parameter estimates.
    • Explore the Bayesian approach to construct a point estimator.
  • Confidence Intervals:

    • Learn to construct confidence intervals on the mean, variance, standard deviation, and population proportions using both normal distribution and t distribution methods.
    • Understand the general method for constructing an approximate confidence interval on a parameter.
    • Discover how to compute a prediction interval for a future observation and create a tolerance interval for a normal population.
  • Hypothesis Testing:

    • Structure decision-making problems as hypothesis tests.
    • Perform hypothesis testing on means, variances, standard deviations, and population proportions using Z-tests or t-tests.
    • Learn to compute the P-value for decisions in hypothesis testing.
    • Understand the relationship between confidence intervals and hypothesis tests.
    • Apply goodness-of-fit tests, contingency table tests, nonparametric tests, equivalence testing, and combined P-values.
  • Comparative Experiments:

    • Structure comparative experiments involving two samples as hypothesis tests.
    • Test hypotheses on the difference in means, variances, or proportions between two normal distributions.
    • Learn to make decisions in two-sample tests using the P-value approach.
  • Regression Analysis:

    • Utilize simple linear regression for empirical modeling of engineering and scientific data.
    • Understand the least squares method for estimating parameters in a linear regression model.
    • Analyze residuals to assess model fit and identify potential violations of assumptions.
    • Test hypotheses and construct confidence intervals on regression model parameters.
    • Use the regression model to predict future observations and construct appropriate prediction intervals.
    • Apply correlation models and understand simple transformations to achieve a linear regression model.

Why Enroll in This Course?

  • Expert Instructor: Learn from Mohamed Sayed El-Ashhab, an expert instructor with extensive knowledge in statistics and probability.
  • Practical Application: Gain hands-on experience by applying statistical methods to real-world problems in engineering and science.
  • Advanced Skills: Elevate your analytical skills to an advanced level, preparing you for high-level decision-making roles.
  • Flexible Learning: Study at your own pace with the convenience of online learning, accessing course materials anytime, anywhere.

Join our Advanced Statistics and Probability Theories course today and transform your understanding of statistical analysis! 📊📚✨

Course Gallery

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5877450
udemy ID
17/03/2024
course created date
15/07/2024
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