how is intro to statistics course dr.vining?

Introduction to Data Literacy

This course covers how to read, understand, manipulate, and use data. There is no prerequisite knowledge for this course, but it does require access to

Introductory Statistics for College Credit

This course will teach you the equivalent of a semester course in introductory statistics.

Statistics 1 – Probability and Study Design

This course, the first of a three-course sequence, provides an introduction to statistics for those with little or no prior exposure to basic probability and statistics.

Statistics 2 – Inference and Association

This course will teach you the use of inference and association through a series of practical applications, based on the resampling/simulation approach, and how to test hypotheses, compute confidence intervals regarding proportions or means, computer correlations, and use of simple linear regressions.

Statistics 3 – ANOVA and Regression

This course, the third of a three-course sequence, provides ananalysis of variance (ANOVA) and multiple linear regression through a series of practical applications.

What are the major topics covered in introductory statistics?

All of the major topics of an introductory level statistics course for social science are covered. Background areas include levels of measurement and research design basics. Descriptive statistics include all major measures of central tendency and... read more

What are the basic topics of statistics?

All of the major topics of an introductory level statistics course for social science are covered. Background areas include levels of measurement and research design basics. Descriptive statistics include all major measures of central tendency and dispersion/variation. Building blocks for inferential statistics include sampling distributions, the standard normal curve (z scores), and hypothesis testing sections. Inferential statistics include how to calculate confidence intervals, as well as conduct tests of one-sample tests of the population mean (Z- and t-tests), two-sample tests of the difference in population means (Z- and t-tests), chi square test of independence, correlation, and regression. Doesn’t include full probability distribution tables (e.g., t or Z), but those can be easily found online in many places.

What order should the topics be presented in a book?

By the nature of the subject, the topics have to be presented in a sequential and coherent order . However, the book breaks things down quite effectively.

Is the statistics textbook comprehensive?

The textbook is indeed quite comprehensive. It can accommodate any style of introductory statistics course.

Is statistical theory universal?

Essentially, statistical concepts at the introductory level are accepted as universal. This suggests that the relevance of this textbook will continue for a long time.

Can you copy and reproduce statistics?

This work is in the public domain. Therefore, it can be copied and reproduced without limitation. However, we would appreciate a citation where possible. Please cite as: Online Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University. Instructor's manual, PowerPoint Slides, and additional questions are available.

Can you copy and reproduce Introduction to Statistics?

This work is in the public domain. Therefore, it can be copied and reproduced without limitation. However, we would appreciate a citation where possible.

What is the purpose of statistics book?

Statistics book covers many statistical fields. Our life is full of events and phenomena that enhance us to study either natural or artificial phenomena could be studied using different fields of science like physics, chemistry, and mathematics . The goal of this book is to connect those concepts with the advanced statistical problems. Statistics is used in a variety fields like business and engineering and science. We can sea there are many applications of statistics in those fields, the applications of statistics are many and varied; people encounter them in everyday life, such as in reading newspapers or magazines, listening to the radio, or watching television. Since statistics is used in almost every field of endeavor, the educated individual should be knowledgeable about the vocabulary, concepts, and procedures of statistics.

What is continuous variable?

Continuous variables assume all values between any two specific values, i.e. they take all values in an interval. They often include fractions and decimals. Definition 1.2.7 In the following we illustrate some examples on a continuous variable

What are variables classified according to?

Variables classified according to how they are categorized or measured. For example, the data could be organized into specific categories, such as major field (mathematics, computers, etc.), nationality or religious affiliation. On the other hand, can the data values could be ranked, such as grade ^A B C D F, , , , h or rating scale (poor, good, excellent), or they can be classified according to the values obtained from measurement, such as temperature, heights or IQ scores. Therefore we need to distinguish between them through the measurement scale used. There are four levels of measurement scales ; nominal , ordinal , interval , and the ratio level of measurement, the difference between these four levels is explained in the following definitions. The nominal level of measurement classifies data into mutually exclusive (disjoint) categories in which no order or ranking can be imposed on the data. Definition 1.2.8 The following examples include nominal level of measurements in different cases.

What is the difference between quantitative and quali tative variables?

Quantitative variables give us quan - titative data and inquires about the phrase “how much”, while the quali - tative variables give us the qualita - tive data and inquires about the phrase “what or what is”.

What is a study based on?

Any study is based on a problem or phenomenon such as heavy traffics, accidents, rating scales and grades or others . The researcher should define the variables of interest before collecting data.

What is an element in statistics?

An element (or member of a sample or population) is a specific subject or object about which the information is collected. Definition 1.2.1 Example 1 below discuss the definition of an element numerically

What is population in statistics?

population is called a sample. In statistical problems we may interest to make a decision and prediction about a population by using results that obtained from selected samples, for instance we may interest to find the number of absent students at PY on a certain day of a week, to do so, we may select 200 classes from PY and register the number of students that absent on that day, then you can use this information to make a decision. The area of statistics that interest on such decision is referred to inferential statistics. Inferential statistics deals with methods that use sample results, to help in estimation or make decisions about the population. Definition 1.1.3 During this section, we will clarify the meaning of population, sample, and data. Therefore, the understanding of such terms and the difference between them is very important in learning statistics. For example, if we interest to know the average weights of women visited diet section in a hospital during specified period of time, then all women who visited that section represents the study population. A population is the set of all elements (observations), items, or objects that bring them a common recipe and at least one that will be studied their properties for a particular goal. The components of the population are called individuals or elements. Definition 1.1.4 Any collection of things, including a joint gathering recipe at least one to be examined for a particular purpose, called a statistically population (or population as a matter of shortcut). The compo - nents of the population are called individuals or elements.