**The following course in Statistics is provided in its entirety by Atlantic
International University's "Open
Access Initiative" which strives to make knowledge
and education readily available to those seeking advancement
regardless of their socio-economic situation, location
or other previously limiting factors. The University's
Open Courses are
free and do not require any purchase or registration,
they are open to the public.**
The course in **Statistics** contains the following:
- Lessons in video format with explaination of theoratical content.
- Complementary activities that will make research more about the topic , as well as put into practice what you studied in the lesson. These activities are not part of their final evaluation.
- Texts supporting explained in the video..
The Administrative Staff may be part of a degree program paying up to three college credits. The lessons of the course can be taken on line Through distance learning. The content and access are open to the public according to the "Open Access" and " Open Access " Atlantic International University initiative. Participants who wish to receive credit and / or term certificate , must register as students.
### Lesson 1:** THE HISTORY OF ALGEBRA**
Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty; and it thereby provides the navigation essential for controlling the course of scientific and societal advances (Davidian, M. and Louis, T. A., 10.1126/science.1218685). Statisticians apply Statistical thinking and methods to a wide variety of scientific, social, and business endeavors in such areas as astronomy, biology, education, economics, engineering, genetics, marketing, medicine, psychology, public health, sports, among many. "The best thing about being a Statistician is that you get to play in everyone else's backyard."
### Lesson 2: THE EQUATIONS
One of the first lessons taught in Algebra is Solving Equations. This is the basis of Algebra and many other lessons taught in Algebra will rely on knowledge of this skill.
So, what is an equation?
An equation is a mathematical statement that shows that two quantities are equal.
**Lesson 3: ANALYTIC GEOMETRY**
We begin to seriously channel Euclid in this tutorial to really, really (no, really) prove things--in particular, that triangles are congruents. You'll appreciate (and love) what rigorous proofs are. It will sharpen your mind and make you a better friend, relative and citizen (and make you more popular in general). Don't have too much fun.
**Lesson 4: DEFINITION & HISTORY OF GEOMETRY**
The Babylonians replaced the older (4000 BC - 2000 BC) Sumerian civilization around 2000 BC. The Sumerians had already developed writing (cuniform on clay tablets) and arithmetic (using a base 60 number system). The Babylonians adopted both of these. But, Babylonian math went beyond arithmetic, and devloped basic ideas in number theory, algebra, and geometry. The problems they wanted to solve usually involved construction and land estimation, such as areas and volumes of rectangular objects. Some of their methods were rules that solved specialized quadratic, and even some cubic, equations.
**Lesson 5: Descriptive Statistics**
Descriptive Statistics are typically distinguished from inferential Statistics. With descriptive Statistics you are simply describing what is or what the data shows. With inferential Statistics, you are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential Statistics to try to infer from the sample data what the population might think. Or, we use inferential Statistics to make judgments of the probability that an observed difference between groups is a dependable one or one that might have happened by chance in this study. Thus, we use inferential Statistics to make inferences from our data to more general conditions; we use descriptive Statistics simply to describe what's going on in our data.
**Lesson 6: ANALYSIS OF DATA AND GRAPHIC OF FREQUENCY DISTRIBUTIONS**
While data analysis in qualitative research can include Statistical procedures, many times analysis becomes an ongoing iterative process where data is continuously collected and analyzed almost simultaneously. Indeed, researchers generally analyze for patterns in observations through the entire data collection phase (Savenye, Robinson, 2004). The form of the analysis is determined by the specific qualitative approach taken (field study, ethnography content analysis, oral history, biography, unobtrusive research) and the form of the data (field notes, documents, audiotape, videotape).
** Lesson 7: PROBABILITY AND Statistics**
Most experimental searches for paranormal phenomena are Statisticsal in nature. A subject repeatedly attempts a task with a known probability of success due to chance, then the number of actual successes is compared to the chance expectation. If a subject scores consistently higher or lower than the chance expectation after a large number of attempts, one can calculate the probability of such a score due purely to chance, and then argue, if the chance probability is sufficiently small, that the results are evidence for the existence of some mechanism (precognition, telepathy, psychokinesis, cheating, etc.) which allowed the subject to perform better than chance would seem to permit.
** Lesson 8: SAMPLING THEORY
StatisticsS
SAMPLING THEORY**
A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection.
**Lesson 9: EXPERIMENTAL DESIGN AND THE VARIANCE**
Deviations about the mean of a population is the basis for most of the Statisticsal tests we will learn. Since we are measuring how widely a set of scores is dispersed about the mean we are measuring variability. We can calculate the deviations about the mean, and express it as variance or standard deviation. It is very important to have a firm grasp of this concept because it will be a central concept throughout the course.
**Lesson 10: CORRELATION AND REGRESSION**
Correlation and linear regression are the most commonly used techniques for investigating the relationship between two quantitative variables. The goal of a correlation analysis is to see whether two measurement variables co vary, and to quantify the strength of the relationship between the variables, whereas regression expresses the relationship in the form of an equation.
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