The formula to find the population mean is: μ = (Σ * X)/ N. where: Σ means “the sum of.” X = all the individual items in the group.

Probability Examples in Real Life

1. Card Games. Have you ever wondered why some poker hands are more valuable than others?
2. Sports Statistics. The world of sports uses statistics to predict the future when it comes to winning games.
3. Natural Disasters.
4. Getting Dressed.
5. Winning the Lottery.
6. Buying Insurance.
7. Predicting the Weather.

Mean: Add up all the numbers of the set. Divide by how many numbers there are. Mode: The number that occurs the most.

Sample Mean is the mean of sample values collected. Population Mean is the mean of all the values in the population. If the sample is random and sample size is large then the sample mean would be a good estimate of the population mean.

The natural population change is calculated by births minus deaths and net migration is the number of immigrants (population moving into the country) minus the number of emigrants (population moving out of the country) – please see example below. In some countries population registers are used instead.

How to calculate the sample mean

1. Add up the sample items.
2. Divide sum by the number of samples.
3. The result is the mean.
4. Use the mean to find the variance.
5. Use the variance to find the standard deviation.

Formula : X = Sum of X values / N(Number of Values) X Bar: The x-bar is used to represent the sample mean; that is, the mean of a sample rather than an entire population. The mean of the entire population is usually represented by the Greek letter mu.

The sample mean from a group of observations is an estimate of the population mean . For example, suppose the random variable X records a randomly selected student’s score on a national test, where the population distribution for the score is normal with mean 70 and standard deviation 5 (N(70,5)).

Mean, variance, and standard deviation The mean of the sampling distribution of the sample mean will always be the same as the mean of the original non-normal distribution. In other words, the sample mean is equal to the population mean.

mutual understanding

U(a,b) uniform distribution. equal probability in range a,b.