Sample and Sampling Distribution

Sample and Sampling Distribution

1. Simpling Distribution

   • Distribution of a sample statistics compited from different samples of the same size from the same population
   • Shows how the sample statistics varies from sample to sample
   • Most used type of samples
     • Simple random sampling
     • Stratified random sampling
     • Multistage random sampling

2. T-Student

   • An estimate of the standard error of the mean of the population
   • How well known is the mean based on the sample size

3. Normal Distribution

   • Population distribution of data is assumed normal.
   • A sample of the population is used to estimate the mean and the standard deviation

4. Chi-Square

   • Determine if there's a relationship between variables where the chance that somthing falls into a particular category depends on whether the variable falls into another category comes into play.

5. F-Functions

   • A continuous probability distribution that arises frequently as the null distribution of a test statistic, most notably in the analysis of variance.

6. Skewness for a normal distribution

   • CERO

7. The kurtosis for a standard normal distribution

   • THREE

8. The Sample Size Calculation is used to determine how big or small your sample needs to be in order to get results that reflect the target population as precisely as needed.

9. The Main Applications of Sampling in Statistical Inference

   • Assumed in general a behavior of a population.