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Grace M.
18 Probability lessons
We covered topics such as conditional probability, counting rules, events, discrete random variable, binomial probability, hypergeometric probability, normal distribution/standard normal distribution, calculating probability using normal table, how to use a T table, normal approximation to the binomial probability, sampling theory, estimation/ statistical test of hypothesis, tests about a population mean, tests for difference between two populations, and test for correlation.
Amanda K.
2 lessons
Statistics
• Review of computations for arithmetic mean, standard deviation, and variance of a sample
• Computation of quadratic mean and harmonic mean of a data set
• Computation of the sample proportion
• Use of the normal distribution to compute a confidence interval for a sample mean
• Compuation of the margin of error for a sample mean
• Use of the Student's t-distribution to compute a confidence interval for a sample mean
• Computation of the number of degrees of freedom when using the t-statistic or the Chi-squared distribution
• Determination of critical values when using the normal distribution, t-distribution, or Chi-squared distribution to compute confidence intervals
• Use of tables for the normal, Student t, and Chi-square distributions
• Probability computations using classical probability theory, i.e. number of successful outcomes divided by the number of possible outcomes
• Probability of consecutive independent events (product of individual probabilities)
• Binomial experiment criteria, and computation of binomial probability
• Approximating the binomial distribution using the normal distribution
Grey S.
3 Probability lessons
We went over topics that included Bayes’ Theorem, probability of repeated independent events, permutations, binomial probability distribution, expected value, variance/covariance, joint probability, and more. He knows every topic extremely well and was able to help me through my struggles. I noticed that my understanding of the material that would be on the midterm increased after working with Daniel, and I decided to do one more session with him before the big test.
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Probability Tutors in Pittsburgh, PA
Probability tutors in Pittsburgh, PA, are available through Wyzant to help students understand and apply probability concepts ranging from basic calculations to advanced statistical modeling. With expert instruction, learners can get personalized support for coursework, SAT/ACT prep, and college-level statistics.
Understanding probability involves learning about chance, likelihood, and data analysis to solve real-world problems. Whether studying for classes or exploring applications like machine learning, students can benefit from targeted guidance that builds confidence and practical skills.
Wyzant connects learners with experienced tutors who offer flexible, one-on-one lessons in probability. By focusing on individual needs and clear teaching, learners can advance their understanding, excel in exams, and apply probability concepts effectively.
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