is a variable whose value depends on the outcome of a probabilistic experiment. Its value is a priori unknown, but it becomes known once the outcome of the experiment is realized.

a variable where chance determines its value.

2 Types of Random Variable

has distinct values that are countable and finite or countably infinite. This data type often occurs when you are counting the number of event occurrence

has values that are uncountably infinite and form a continuous range of values. They can take on any value within a range. In fact, there are infinite values between any two values. This data type often occurs when you measure a quantity on a scale.

Is a collection, or set, of individuals, objects, or measurements whose properties are to be analyzed. It is the totality of the observation.

Is a subset of a population. It is a smaller group representing the population having identical characteristics from which it was taken. A sample is taken since the study of a complete population may be too costly, time-consuming, and full of unpredictable inaccuracies.

Is a numerical measurement describing some characteristic of a population

the sample is a proportion of the population and such sample is selected from the population by means of systematic way in which every element of the population has a chance of being included in the sample.

3 Types of Probability Sampling

This is a technique of sampling in which every nth name in the list may be selected to be included in the sample which serves a random start.

It is a more efficient sampling procedure wherein the population is grouped into a more or less homogeneous classes or strata in order to avoid the possibility of drawing samples whose members come from one stratum.

the sample size of each stratum is equal to the subgroupʼs proportion in the population as a whole.

It is sometimes called area sampling because it is applied on geographical basis. it will give more precise results particularly when each cluster contains a more varied mixture and when one cluster is nearly like the other.

the sample is not a proportion of the population and there is no system in selecting the sample. The selection depends on the situation

(3) Different Types of Non-Probability Sampling

It is based on certain criteria laid down by the researcher. People who satisfy the criteria are interviewed. it is determining the target population of those who will be taken for the study. The respondents are chosen on the basis of their knowledge of the information desired.

Is a process of picking out people in the most convenient and fastest way to get reactions immediately.

This type of sampling specified number of persons of certain types included in the sample. In many sectors of the population are represented. However, the representation is doubtful are no guidelines in the selection of the respondents

The process of using a sample to make inferences about a population

Characteristics such as the population mean, the population variance, and the population proportion

Characteristics of the sample such as the sample mean, the sample variance, and the sample proportion

is a formula for estimating a parameter

is a particular value that we calculate from a sample by using an estimator.

2 types of Estimate

is a value of a sample statistics that is used as a single estimate of a population parameter

is a range of values that brackets the population parameter with some probability

Interval estimates of population parameters

measures the preciseness of an estimate of a population mean

measures the half width of a confidence interval for a population mean

is used to assess how precise some estimate is of a population proportion or a population mean.

is the standard deviation of a sampling distribution