Hypothesis testing for Normal Distribution – Critical values method (3 examples)
Critical values method In this tutorial, we work through 3 examples of using the critical value method to determine, determine whether to accept or reject the null hypothesis.
Understanding Critical values (Hypothesis testing for Normal Distribution)
In this tutorial, we learn how about critical value, critical regions and how to use them to determine whether to accept or reject the null hypothesis.
Hypothesis testing for Normal distribution (One tailed and 2 tailed test)
Hypothesis testing for Normal distribution In this tutorial, we do more examples of hypothesis testing for one-tailed and two-tailed tests using the p values method.
Introduction to Hypothesis testing for Normal distribution
Introduction to Hypothesis testing for Normal distribution In this tutorial, we learn how to conduct a hypothesis test for normal distribution using the p values method with 6 simple steps.
Sampling distribution of the sample means (Normal distribution)
Sampling distribution of the sample means (Normal distribution) In this tutorial, we learn about the sampling distribution of sample means for normal distribution.
Sampling distribution of the sample means (Normal distribution) proof
Sampling distribution of the sample means (Normal distribution) proof In this tutorial, we learn how to prove the result for the sampling distribution of sample means from a normal distribution.
The Wilcoxon sum rank test
The Wilcoxon signed rank test
The sign test
What is a non-parametric test?
Chi-squared test for goodness of fit for a Normal distribution
Chi-squared test for goodness of fit for a Geometric distribution
Chi-squared test for goodness of fit for a Discrete Uniform distribution
Chi-squared test for goodness of fit for a Poisson distribution
Chi-squared test for goodness of fit for a Binomial Distribution
Large sample taken from any population with unknown variance
Large sample taken from any population with known variance
Sample taken from a normal distribution with known population variance
Large sample drawn from any population with unknown variance
Large sample drawn from any population with known variance
Sample drawn from a normal distribution with known population variance
Unbiased estimator for the population variance
Unbiased estimator for the population mean
The distribution of the sample mean
More than two independent normal random variables
Linear Combinations of Normal Random Variables
The Sums and Differences of Normal Variables
E[g(x)]
Related Random Variables
Be able to find and use the cumulative distribution functions of related variables. e.g. Given the c.d.f. of X, find the c.d.f. of Y and hence the p.d.f. of Y where Y = X3
Combining means and variances from distributions
Yates continuity correction
Discrete uniform distribution
Exam Questions – Discrete random variables
These questions are from another board but may help in your revision
Hypothesis testing for Spearman’s correlation coefficient
Inverse Normal Function to find observed values
Normal Cumulative Distribution Function
The variance Var(X) – Geometric Distribution
Binomial probabilities on a calculator
Hypothesis testing for zero correlation
Measuring linear correlation using a calculator
Expected values E(X²)
Central Limit Theorem
Exam Questions – Calculating the mean and standard deviation
Exam Questions – Finding an observed value
Chi squared test for contingency tables
Sum of two Poisson distributions
Var(aX + bY) = a2Var(X) + b2Var(Y)
E(aX + bY) = aE(X) + bE(Y)
Exam Questions – Spearman’s Rank Correlation Coefficient
Spearman’s rank correlation coefficient
Probability using permutations and combinations
In this video, I show you how to use permutations and combinations to work out probabilities. A committee of 5 people is to be selected from a group of 5 men and 6 women. What is the probability that the committee contains 2 men and 3 women? Each of 5 cards has one of the […]