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STATISTICS 243 FORMULAS 8 Source: Rachel L. Webb, PSU, January 2018 Learning Center 1875 SW Park Avenue, Millar Library, Portland, OR 97201 503.725.4448 www.pdx.edu ...
Aug 17, 2023 · 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.
d3bxy9euw4e147.cloudfront.net · oscms-prodcmsIntroductory Statistics - d3bxy9euw4e147.cloudfront.net
OpenStax CNX provides students with free online and low-cost print editions of the OpenStax College library and provides instructors with tools to customize the content so that they can have the perfect book for their course.
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Basic Statistics Definitions: Statistics – Practice or science of collecting and analyzing numerical data. Data – Values collected by direct or indirect observation. Population – Complete set of all observations in existence. Sample – Slice of population meant to represent, as accurately as possible, that population.
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- MADE EASY
- The First Edition
- The Second Edition
- PREFACE
- Statistical Concepts
- Definition 1.1.1
- A Descriptive Statistics
- Definition 1.1.2
- Definition 1.1.3
- Definition 1.1.4
- Remark
- Example 1
- Definition 1.1.5
- Variables and Types of Data
- Example 1
- Definition 1.2.2
- Definition 1.2.3
- X(C)=11.
- Definition 1.2.4
- Definition 1.2.5
- The following table shows some examples of the two types of variables
- Definition 1.2.6
- Definition 1.2.7
- Definition 1.2.8
- Example 6
- Definition 1.2.9
- Example 7
- Definition 1.2.10
- Definition 1.2.11
- Example 9
- Sampling Techniques
- A Simple Random Sampling Method
- C Stratified Sampling Method
- Example 3
- D Cluster Sampling Method
- Observational and Experimental Studies
- Exercises On Chapter One
- Remark
- Raw Data
- Definition 2.1.1
- Organizing and Graphing Qualitative Data
- A Frequency Table:
- Definition 2.2.1
- Construct a Frequency Distribution Table
SECOND EDITION Prof. Dr. Hamid Al-Oklah Dr. Said Titi Mr. Tareq Alodat ii
The main objective of this book is to provide students of Preparatory Year Deanship, at King Saud University in Saudi Arabia, a textbook in statistics. In fact, we found that most of the university statistics books are almost too much pages long, contain more material than can reasonably be covered in one term, and they are not readable for most...
Based on the directives of the Department of Basic Sciences at the Deanship of the preparatory year in to develop some of the decisions of the books studied by the students of the preparatory year at King Saud University, it has included the development of the book Introduction to Statistics for authors Dr. Said Titi, Khaled Khashan and Mr. Tareq A...
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...
Our life is full of events and phenomena that enhance us to study either natural or artificial phenomena could be studied using different fields one of them is statistics. For example, the applications of statistics are many and varied as follows: -People encounter them in everyday life -Reading newspapers or magazines, -Listening to the ...
Statistics is a branch of science dealing with collecting, organizing, summarizing, analysing and making decisions from data. Statistics is divided into two main areas, which are descriptive and inferential statistics.
Suppose that a test in statistics course is given to a class at KSU and the test scores for all students are collected, then the test scores for the students are called data set (the definition of this term will be discussed deeper in section 1.2). Usually the data set is very large in the original form and it is not easy to use it to draw a conclu...
Descriptive statistics deals with methods for collecting, organizing, and describing data by using tables, graphs, and summary measures.
Inferential statistics deals with methods that use sample results, to help in estimation or make decisions about the population. 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 int...
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.
Note that a population can be a collection of any things, like Ipad set, Books, animals or inanimate, therefore it does not necessary deal with people. 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 comp...
In a study of the average number of students in secondary schools in Riyadh city, where there are different stages of the students, such as first, second and third secondary, as well as there are male and female, but they all gathered, including prescription study in high school. Therefore, we find that high school students in Riyadh make up a popu...
A sample is a subset of the population selected for study. Referring to the example of interest to know the average weight of women that visited diet section, in this case the registered weights of some women represent a sample. In practical life there are many ways to get a sample from the popu-lation under study, for example; face-to-face intervi...
Basic terms that will be used frequently in this section, and they are very important tools in statistical problems, such terms are, an element, a variable and their types, a measurement, and a data set, Therefore to understand such terms, it is necessary to illustrate the following definitions.
The following table gives the number of snake bites reported in a hospital in 3 cities (A, B, C). Each one of the cities is a member, that is; city A is a member, city B is a member, and also city C is a member. Remark Any study is based on a problem or phenomenon such as heavy traffics, accidents, rating scales and grades or others. The researcher...
A variable is a characteristic under study that takes different values for different elements. For example, if we collect information about income of households, then income is a variable .These households are expected to have different incomes; also, some of them may have the same income. Note that a variable is often denoted by a capital letter l...
The value of a variable for an element is called an observation or measurement. The following is an example to explain the difference in the meaning between variable and the measurement. Remark 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 a...
We know that the variable is a characteristic under study that takes different values for different elements. In statistics, we have two types of variables according to their elements; first type is called quantitative variable and the second one is called qualitative variable. When a subject can be measured numerically such as (the price of a shir...
Quantitative variable gives us numbers representing counts or measurements. When a subject cannot be measured numerically such as (eye color), then the subject in this case is qualitative variable. The following definition provides us with this concept.
Qualitative variable (or categorical data) gives us names or labels that are not numbers representing the observations. The following examples illustrates the two type of variables
Moreover, the variables measured in quantitative data divided into two main types, discrete and continuous. A variable that assumes countable values is refer to discrete variable, otherwise the variable is a continuous one. Accordingly, we provide the following definitions.
Discrete variables assume values that can be counted. In following we illustrate some examples on a discrete 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. In the following we illustrate some examples on a continuous variable
The nominal level of measurement classifies data into mutually exclusive (disjoint) categories in which no order or ranking can be imposed on the data. The following examples include nominal level of measurements in different cases.
Gender: Male, Female. Eye color: Black, Brown, Blue, Green, ... Religious affiliation: Muslim, Christian, Jew, ... Nationality: Saudi, Syrian, Jordanian, Egyptian, Pakistani, ... Scientific major field: statistics, mathematics, computers, Geography, ... When the classification takes ranks into consideration, the ordinal level of measurement is pref...
The ordinal level of measurement classifies data into categories that can be ordered, however precise differences between the ranks do not exist. The following examples include some ordinal level of measure-ments.
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
Identify the variable and their categories. Record the categories, names or labels in the first column (or rows) of a table Mark a tally, denoted by the symbol / in the second column, next to the corresponding category, name as label. Record the total of the tallies for each category in the third column, which is called the column of frequencies an...
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An event is the speci cation of the outcome of a trial. An event can consist of a single outcome or a set of outcomes. The complement of an event is everything in the sample space that is not that event (not E or E). The probability of an event is always between 0 and 1.
DESCRIPTIVE/SUMMARY STATISTICS. Discipline of quantitatively describing the main features of a collection of data. Numerical and graphical summaries used to characterize a dataset. The three main measures are.
