Introduction to Statistics | Lesson 1

Statistics

This is the science that studies data to be able to make a decision. This involves collecting, processing, summarizing and analyzing data in order to provide answers or solutions to an inquiry.

Qualitative and Quantitative

What are the two broad classifications of variables?

Qualitative Variable

This expresses a categorical attribute, such as sex, religion, marital status, region of residence, highest education attainment. They do not strictly take on numeric values.

Qualitative Variable

Sometimes, there is a sense of ordering in this data. Like income data grouped into high, middle, and low-income status

Quantitative Variable

These are variables where sizes are meaningful, and answers questions such as how much or how many.

Qualitative Variable

This variable answers the questions “what kind”

Quantitative Variable

These variables have actual units of measure, they include height, weight, number of registered cars, household size and total household expenditures.

Discrete and Continuous Variable

What are two variables under quantitative variable?

Discrete Variable

These are data that can be counted, and can assume a finite or infinite countable number of values. An example is the number of days, ages of survey respondents to the nearest year, and such.

Discrete Variables

These are variables whose values or levels cannot take the form of decimals.

Discrete Variables

These are the variables that data can be taken through the process of enumeration or counting.

Continuous Variables

These are variables that can be measured (exact height, exact volume of liquid)

Continuous Variables

These are variables whose levels can take continuous values or assume a continuous set of numerical values.

Nominal, Ordinal, Interval and Ratio

What are the four levels of measurement of numerical data?

Ordinal Data

These are quantities where the numbers are used to designate the rank order of the data.

Ordinal Data

In this type of data, the correlation or the effect ranking of one variable can be measured. But the range for each rank is not constant. An example of these are ranking of pageants, educational attainment, race ranking and such.

Interval Data

This is the data type where the range between the numeric values is constant. In this data, type addition and subtraction can be performed.

Interval Data

We can use this to determine the information on describing the level of the academic performance of students in mathematics or academic performance of students

Ratio Data

This is numerical data in science and engineering, they are expressed in numbers and the difference between two numbers are consistent. But it starts from a TRUE ZERO.

Ratio Data

An example of this numerical data is length, mass, angles, charge, energy, frequency, velocity, and etc.