Introduction to Statistics PDF
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This document introduces the fundamental concepts of statistics, including definitions of key terms such as variables, parameters, and distributions as well as various examples of different kinds of data types. It also explores the different types of variables, providing explanations and examples for categorical and continuous data.
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PRAYER BEFORE CLASS Dear God, Thank you for this day and the opportunity to learn. Please help us to be good listeners and pay attention to our teachers. Help us remember what we are about to learn and use it to make the world a better place. Amen Definition and Field of Statistics Definit...
PRAYER BEFORE CLASS Dear God, Thank you for this day and the opportunity to learn. Please help us to be good listeners and pay attention to our teachers. Help us remember what we are about to learn and use it to make the world a better place. Amen Definition and Field of Statistics Definition of related terms Types of variables OBJECTIVES The learner shall be able to: a. interpret in his own words the meaning of statistics and related terms. b. discuss variables according to function, measurement of values, continuity of value and scale of measurements c. identify whether a variable is dependent or independent, qualitative or quantitative, discrete or continuous, nominal, ordinal, interval or ratio. What is Statistics? It is the process of collecting data, classifying data, representing data for easy interpretation, and further analysis of data. 4 What is the importance of Statistics in Data Analysis? Statistical tools for data interpretation Role of statistics in research Applications of statistics in various fields 5 STATISTICAL TERMS ❏ UNIVERSE ❏ Set of all entities under study ❏ POPULATION ❏ Total or entire group of individuals or observations from which information is desired by a researcher ❏ SAMPLE ❏ Subset of the population ❏ STATISTICS ❏ Numerical summary of a sample ❏ INDIVIDUAL ❏ Person or object that is a member of the population being studied 6 STATISTICAL TERMS ❏ Variable ❏ Any characteristics of an individual or entity ❏ It can be categorical or quantitative ❏ PARAMETER ❏ A numerical summary of a population ❏ DISTRIBUTION ❏ Tells what values the variable takes and how often it takes these values ❏ DESCRIPTIVE STATISTICS ❏ Describe data through numerical summaries, tables and graphs ❏ INFERENTIAL STATISTICS ❏ Uses methods that take a result from a sample, extend it to the population, and 7 measure the reliability of the result Nature of Statistics ▶ Descriptive Statistics – includes techniques which are concerned with summarizing quantitative data. This method makes use of graphical or computation of data. It is used to present data in a convenient, usable, and understandable form ▶ Inferential Statistics – Considered higher form of statistics, for it does not only describe the characteristics of the data observed, but it also make used of logical reasoning in order to find or established cause and effect relationship. It make used of one’s judgment based on the behavior of the sample being observed. 8 Classification of Statistics Parametric Statistics – an approach that assumes a random sample from a normal distribution and involves testing a hypothesis about the population parameter. Non-Parametric Statistics – statistical approach for estimating and hypothesis testing when no underlying data distribution is assumed or is often called the distribution-free method. Can be used for nominal and ordinal-scaled data. It is also appropriate if there is not enough sample size to assess the form of the distribution. 9 Data ▶quantities (numbers) or qualities (attributes) measured or observed that are to be collected and/or analyzed. A collection of data is called data set. Types of Data 1. Categorical data – nominal and ordinal scale ▶ Nominal scale – consists of a finite set of possible values or categories that have no particular order. Might be stored using number rather than text but the numbers have no meaning. They are labels only. Examples: cause of death (cancer, heart attack, accident, etc.), gender (male, female), mode of transportation, nationality, occupation, civil status and so on. ▶ Ordinal scale – ordered scales. Consists of finite set of possible values or categories which do have an order. Examples: pain level (none, mild, moderate, severe) social status, attitude toward a subject and so on. Types of Data 2. Continuous data – interval and ratio, parametric statistics. ▶ Interval scale – generally measured on a continuum and differences between any two numbers on the scale are of known size. There is no true zero point. That is, the value “0” is arbitrary and does not reflect absence of the attribute. Example: temperature – a temperature of zero does not mean there is no temperature, tons of garbage, number of arrest, income, age and so on. ▶ Ratio scales – both equal intervals and an absolute zero point. It is also measured on a meaningful continuum. It has a meaningful zero point. Highest or most precise scaled- data. Examples: weight in pounds, height in centimeters, age in years. Variables ▶any characteristic, number, or quantity that can be measured or counted. ▶three kinds of variables: independent, dependent, and controlled. Examples: smoking habit, attitude, toward the head, height, faculty ranks and so on. Types of Variables 1. Qualitative variable – represent difference in the quality, character or kind but not in amount. Variables that yield non-numeric. Example: sex, birthplace, geographic location, religion, marital status, socio-economic status, educational attainment, eye color, race and etc. Types of Variables 2. Quantitative variable – are numerical in nature and can be ordered or ranked. Example: weight, height, age, grades, test scores, body temperature, and others of the like. Classification of Quantitative variable 1. Discrete – variable whose values can be counted using integral value such as number of enrollees, salary of teachers, length of service, birth, death, marriage. 2. Continuous – variables that can be assume a numerical value over an interval such as height, weight, speed, pressure, and body temperature 17 FORMATIVE ASSESSMENT 1. What is Statistics? Explain in your own words 2. Determine the type of data and scale of the following a) Male and female b) Rank of students in the class c) Age 3. Jenna is researching the College of Accountancy and wanted to summarize the frequency of girls and boys enrolled in the program. What nature of statistics did Jenna use? 4. While John is making a table for his research, he replaces the label with numbers in creating the categories of his data. What type of data did John use? 5. Determine the independent and dependent variable: a) How does the time of studying affect the score on examination? b) Does traffic affect the mood of a passenger? c) Study on the relationship between screen time and sleep. 18