What Is Math?
Statistics is the science of collecting, organizing, presenting, analyzing and interpreting numerical facts that are used in making decisions. It is a discipline of mathematics that incorporates linear algebra, calculus, probability theory, and statistical analysis.
(Searching for “MyOpenMath answers“? Visit our website!)
The term “statistics” was first used in the 16th century by German etymologist Ferdinand de Saussure to describe the study of political polling and election results. This definition, however, has broadened over time to include many areas of data analysis and evaluation.
What Is Math?
Mathematics is the science of numbers, space, and quantity. It is usually studied in a classroom and is often applied to real-life situations. It is a general and widely used subject, involving everything from simple arithmetic to complicated calculus and engineering.
What are statistics?
Statistics is a discipline of applied mathematics that originated with the application of mathematical tools including calculus and linear algebra to the field of probability theory. It uses a combination of these disciplines to interpret, analyze, and forecast data.
A Statistic is a person who studies and collects statistical information. They then use that information to make decisions and solve problems.
They also use their knowledge of statistical methods to educate others on how to use statistics effectively in their work. They are a valuable part of any business or industry that relies on statistics.
How does the science of statistics differ from other fields of study?
While most of the other sciences focus on proofs of theorems, statisticians are motivated by applications. They want to develop good methods for analyzing data and making decisions, not just prove theorems that they can then use to justify their work.
There are two main types of statistics: descriptive and analytical. Descriptive statistics are based on the representation of data, while analytical statistics are based on the calculation of statistical parameters.
Nominal Level Measurement
Nominal level measurements are simply labels or categories assigned to other variables. For example, a car can be described as having a make, model, year, mileage, color, or condition.
Depending on the type of data, these nominal-level measurements can be very different from the numerical descriptors we are familiar with such as mean and standard deviation.
Sampling
In some cases, it may not be possible to gather the exact information that is needed for a particular analysis. In these instances, sampling techniques are used to gather representative subsets of the population that can be analyzed more easily.
Examples of sampling techniques include random, systematic, stratified, and cluster sampling.
What is the difference between Descriptive and Inferential Statistics?
The main difference between the two is those descriptive statistics describe basic features and characteristics of the sample data. Inferential statistics, on the other hand, infer new or uncollected numbers from the sample data. These techniques can be used to answer questions such as how much a company should pay its employees or how much a car should cost in the market.