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LESSON I - INTRODUCTION

PAMANTASAN NG LUNGSOD NG MAYNILA (University of the City of Manila) Gen. Luna cor. Muralla Sts., Intramuros, Manila. FUNDAMENTALS OF STATISTICS. LESSON I - INTRODUCTION. Dr. Rebecca C. Tolentino. OUTLINE. I Introduction Definition of Statistics Statistical Method

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LESSON I - INTRODUCTION

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  1. PAMANTASAN NG LUNGSOD NG MAYNILA (University of the City of Manila) Gen. Luna cor. Muralla Sts., Intramuros, Manila FUNDAMENTALS OF STATISTICS LESSON I - INTRODUCTION Dr. Rebecca C. Tolentino

  2. OUTLINE • I Introduction • Definition of Statistics • Statistical Method • History and Importance of Statistics • Definition of Basic Terminology • Types of Data • Population and Sample • Sampling Methods

  3. BASIC CONCEPTS IN STATISTICS

  4. What is Statistics? • Statisticsis the science of collecting, organizing, presenting, analyzing, and interpreting quantitative or numerical data.

  5. Statistics • Branch of mathematics • Course of study • Facts and figures • Measurement taken on a sample

  6. Why study statistics? • Numerical information is everywhere. Statistics will be very useful in order to understand and process these numerical information. • Statistical Techniques are used to make decisions that affect our daily lives. • Knowledge of statistical methods will help you understand how decisions are made and give you a better understanding of how they affect you. Source: Lind, D.A., Marchall, W.G. & Wathen, S.A. , Basic Statistics for Business & Economics 5th Edition

  7. Basic terminologies

  8. VARIABLES AND CONSTANT • CONSTANT- Characteristics of objects, people, or events that does not vary. • VARIABLE -A variable is a characteristic or condition that can change or take on different values.

  9. Population and Sample • POPULATION- The entire group of individuals, objects, or measurements of interest. • SAMPLE - a subset, or part, of the population of interest • Usually populations are so large that a researcher cannot examine the entire group. Therefore, a sample is selected to represent the population in a research study. The goal is to use the results obtained from the sample to help answer questions about the population.

  10. Population vs Sample population A F E Y L B Z M N Q R C D X V K P W G U P O T J S I H From: Sirug, Basic Statistics sample

  11. Descriptive vs. Inferential Statistics • Descriptive Statistics uses data gathered on a group to describe or reach conclusions about that same group only. • Descriptive statistics gives numerical or graphics procedures to summarize a collection of data in a clear and understandable way. • Helps us to simplify large amount of data in a sensible way.

  12. Inferential Statistics • Inferential Statistics uses sample data to reach conclusions about the population from which the sample was taken • Provides procedures to draw inferences about a population from a sample.

  13. Parameter vs. Statistic • Parameter — descriptive measure of the population • Usually represented by Greek letters • Statistic — descriptive measure of a sample • Usually represented by Roman letters

  14. Types of Data

  15. Levels of Measurement • Nominal • Ordinal • Interval • Ratio

  16. Nominal data • Data that is classified into categories and cannot be arranged in any particular order . Gender : 0 – Male 1- Female Religion: 1 – Catholic 2 – Islam 3- Protestant 4 – Baptist 5 - Others

  17. Ordinal data data arranged in some order, but the differences between data values cannot be determined or are meaningless. • Position within an academic organization • 1 for President • 2 for Vice President • 3 for Dean • 4 for Department Chair • 5 for Faculty member

  18. Interval Data • Distances between consecutive integers are equal • Relative magnitude of numbers is meaningful • Differences between numbers are comparable • Location of origin, zero, is arbitrary Examples: • Temperature on the Fahrenheit scale. • Intelligence Quotient

  19. Ratio Scale • Highest level of measurement • Relative magnitude of numbers is meaningful • Differences between numbers are comparable • Location of origin, zero, is absolute (natural) • Examples: • Height, Weight, and Volume • Monetary Variables, such as Profit and Loss, Revenues, and Expenses • Financial ratios

  20. Data Level Meaningful Operations Statistical Methods Nominal Ordinal Interval Ratio Classifying and Counting All of the above plus Ranking All of the above plus Addition, Subtraction All of the above plus Multiplication, and Division Nonparametric Nonparametric Parametric Parametric Data Level, Operations, and Statistical Methods

  21. Activity 1

  22. Look at the data available in the PT Clinic and find examples of each Level of measurements.

  23. COLLECTION OF DATA • Types of Data According to Source • Primary Data – data that comes from original source • Data from personal accounts • Secondary Data – data that has been previously gathered by other individuals or agencies • Data from newspapers, pamphlets, books

  24. Methods of Data Collection • Direct or Interview Method-person to person exchange between the interviewer and the interviewee • Indirect or Questionnaire Method-written responses are given to prepared questions • Registration Method-enforced by certain laws/rules • Observation Method • Experiment Method

  25. Data presentation • Textual Method – data is presented in paragraph form • Tabular Method- data is presented in rows and columns • Graphical Method – data is presented in visual form

  26. Ungrouped Versus Grouped Data • Ungrouped data • have not been summarized in any way • are also called raw data • Grouped data • have been organized into a frequency distribution

  27. Frequency Distribution A Frequency Distribution is a grouping of data into mutually exclusive categories showing the number of observations in each class.

  28. EXAMPLE 1 Dr. Tillman is Dean of the School of Business Socastee University. He wishes prepare to a report showing the number of minutes per week students spend studying. He selects a random sample of 30 students and determines the number of minutes each student studied last week. Organize the data into a frequency distribution.

  29. PRESENTATION OF DATA

  30. Line Graphs Line graphs are typically used to show the change or trend in a variable over time.

  31. Example 3 continued

  32. Bar Chart A Bar Chart can be used to depict any of the levels of measurement (nominal, ordinal, interval, or ratio). • Construct a bar chart for the number of unemployed per 100,000 population for selected cities during 2001

  33. Bar Chart for the Unemployment Data

  34. Pie Chart A Pie Chart is useful for displaying a relative frequency distribution. A circle is divided proportionally to the relative frequency and portions of the circle are allocated for the different groups. A sample of 200 runners were asked to indicate their favorite type of running shoe. Draw a pie chart based on the following information.

  35. Pie Chart for Running Shoes Pie Chart for Running Shoes

  36. Exercise

  37. Thank you! For further questions/comments: beck_tolentino@yahoo.com

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