Beginner to Advanced Statistics Tutorials: Beginner to Advanced This page is a complete repository of statistics tutorials which are useful for learning basic, intermediate, advanced Statistics and machine learning algorithms with SAS and R. It covers some of the most important modeling and prediction techniques, along with relevant applications.

In statistics, a variable has two defining characteristics: A variable is an attribute that describes a person, place, thing, or idea. The value of the variable can "vary" from one entity to another. Your browser does not support HTML5 video.

If you view this web page on a different browser e. Quantitative Statics tutorial Variables can be classified as qualitative aka, categorical or quantitative aka, numeric.

Qualitative variables take on values that are names or labels. The color of a ball e. Quantitative variables are numeric. They represent a measurable quantity.

For example, when Statics tutorial speak of the population of a city, we are talking about the number of people in the city - a measurable attribute of the city. Therefore, population would be a quantitative variable.

In algebraic equations, quantitative variables are represented by symbols e. Continuous Variables Quantitative variables can be further classified as discrete or continuous.

If a variable can take on any value between its minimum value and its maximum value, it is called a continuous variable; otherwise, it is called a discrete variable. Some examples will clarify the difference between discrete and continouous variables. Suppose the fire department mandates that all fire fighters must weigh between and pounds.

Suppose we flip a coin and count the number of heads. The number of heads could be any integer value between 0 and plus infinity.

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Introduction to Statistics What is Statistics? |

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Video Tour Core Tutorial Problem Drill Cheatsheet AudioBook Printable This rapid learning course is designed for high school students who are taking the college board's AP Statistics course and also planning on taking the exit exam upon its completion. This rich-media series will provide a much easier learning into this subject and it is ideal for home schooling or in-class course companion. |

Random variables |
Hypothesis Testing Descriptive Statistics Descriptive statistics allow a researcher to describe or summarize their data. For example, descriptive statistics for a study using human subjects might include the sample size, mean age of participants, percentage of males and females, range of scores on a study measure, etc. |

However, it could not be any number between 0 and plus infinity. We could not, for example, get 2. Therefore, the number of heads must be a discrete variable.

Bivariate Data Statistical data are often classified according to the number of variables being studied. When we conduct a study that looks at only one variable, we say that we are working with univariate data. Suppose, for example, that we conducted a survey to estimate the average weight of high school students.

Since we are only working with one variable weightwe would be working with univariate data.

When we conduct a study that examines the relationship between two variables, we are working with bivariate data. Suppose we conducted a study to see if there were a relationship between the height and weight of high school students. Since we are working with two variables height and weightwe would be working with bivariate data.

Test Your Understanding Which of the following statements are true? All variables can be classified as quantitative or categorical variables. Categorical variables can be continuous variables. Quantitative variables can be discrete variables.Introduction to Probability and Statistics Using R Third Edition G.

Jay Kerns An Introduction to Statistics. Get started organizing and interpreting data with these beginner's guides to statistics. Learn basic probability, how to identify features of a dataset, and much more.

These tutorials are designed to show essential data analysis techniques using a spreadsheet program such as Excel. Follow the tutorials in sequence to learn the fundamentals of using a spreadsheet program to organize data, use formulae and functions to calculate statistical values including mean.

Statistics Tutorial: Step by Step Guide Statistics / Analytics Tutorials with SAS, R and Python The following is a list of tutorials which are ideal for both beginners and advanced analytics professionals.

Learn statistics and probability for freeâ€”everything you'd want to know about descriptive and inferential statistics. Full curriculum of exercises and videos.

Learn for free about math, art, computer programming, economics, physics, chemistry, biology, medicine, finance, history, and more. Statistics Tutorial for Beginners - Learn Statistics in simple and easy steps starting from basic to advanced concepts with examples including basic statistics and maths concepts and examples covering individual series, discrete series, continuous series in simple and easy steps.

Introduction to Probability and Statistics | Mathematics | MIT OpenCourseWare