Statistics class

### What is Statistics

the science of planning studies and experiments, obtaining data, and then organizing, summarizing , presenting, analyzing, interpreting, and drawing conclusions based on the data.

### Population

the complete collection of all individuals (scores, people, measurements, and so on) to be studied. the collection is complete in the sense that it includes all of the individuals to be studied.

### Categorical (or qualitative or attribute) data

consist of names or labels that are not numbers representing counts or measurements

### Discrete Data

results when numbers of possible values is either a finite number or a "countable" number (WHOLE NUMBERS)

### Continuous (numerical) Data

results from infinitely many possible values that corresponds to some scale that covers a range of values with gaps, interruptions, or jumps (1.2, 50.4, 100.5 etc..)

### Nominal level of measurement

characterized by data that consist of names, labels, or categories only. The data cannot be arrange in a an ordering scheme (such as low to high)

### Ordinal level of measurement

can be (data) arranged in some order, but differences (obtained by subtraction) between data values either cannot be determined or are meaningless

### Interval level of measurments

is like the ordinal level, with the additional property that the difference between any data value is meaningful. However, data at this level do not have a natural zero starting point. Years (1976, 1977, 1978, 1979), body temperatures 98.2, 100.1 etc..

### Ratio level of measurement

is the interval level with the additional property that there is also a natural zero starting point (where zero indicates the none of the quantity is present). For values at this level, differences and ratios are both meaningful. (Distances and Prices)

### Random Sampling

Random sampling is the method that most closely defines probability sampling. Each element of the sample is picked at random from the given population such that the probability of picking that element can be calculated by simply dividing the frequency of the element by the total number of elements in the population. In this method, all elements are equally likely to be picked if they have the same frequency.

### Systematic Sampling

Systematic sampling is the method that involves arranging the population in a given order and then picking the nth element from the ordered list of all the elements in the population. The probability of picking any given element can be calculated but is not likely to be the same for all elements in the population regardless of whether they have the same frequency.

### Stratified Sampling

Stratified sampling involves dividing the population into groups and then sampling from those different groups depending on a certain set criteria.

For example, dividing the population of a certain class into boys and girls and then from those two different groups picking those who fall into the specific category (age, etc) that you intend to study with your sample.

### Cluster Sampling

Cluster sampling involves dividing up the population into clusters and assigning each element to one and only one cluster, in other words, an element can't appear in more than one cluster.