Chapter 1 Lect 1.pdf
- 2. Preface What is Statistics? Statistics is not just about analyzing the data. It’s about the whole process of using the scientific method to answer questions and make decisions. That process involves designing studies, collecting good data, describing the data with numbers and graphs, analyzing the data, and then making conclusions. 4/3/2023 2
- 3. What is Statistics? Statistics is a way to get information from data data” 4/3/2023 3 Data Statistics Information Data: Facts, especially numerical facts, collected together for reference or information. Information: Knowledge communicated concerning some particular fact. Statistics is a tool for creating new understanding from a set of numbers.
- 4. Why do you analyse data? 1- To choose the correct statistical technique. 2- to compute the statistics. 3- to interpret the statistical results. Stage 2 can be done manually to help students to understand techniques and concepts, or using Excel, Minitab, or SPSS. Stage 1&3 provide students with practical skills to apply to real problems. 4/3/2023 4
- 5. • Selecting the right technique depends on the problem objective & data type. • We are going to focus on how the techniques and concepts introduced are applied to real- world problems. 4/3/2023 5
- 6. Descriptive Statistics It deals with methods of organizing, summarizing, and presenting data in a convenient and informative way, using graphical techniques that make it easy to extract useful information, or numerical techniques to summarize data. Selecting the appropriate technique depends on what specific information we would like to extract. 4/3/2023 6
- 7. Inferential Statistics It is a body of methods used to draw conclusions or inferences about characteristics of populations based on sample data. 4/3/2023 7
- 8. Key Statistical Concepts… • Population — A population is the group of all items of interest to a statistics practitioner. — frequently very large; sometimes infinite. E.g. All 5 million Florida voters can vote on election day _ A descriptive measure of a population is called a parameter. _ In most applications, the parameter represents the information we need. 4/3/2023 8
- 9. • Sample — A sample is a set of data drawn from the population. — Potentially very large, but less than the population. E.g. a sample of 765 voters who exit the polling booth on an election day. _ A descriptive measure of a sample is called a statistic. _ We use statistics to make inferences about parameters. 4/3/2023 9
- 11. Statistical Inference… Statistical inference is the process of making an estimate, prediction, or decision about a population based on a sample data. 4/3/2023 11 Parameter Sample Statistic Inference What can we infer about a Population’s Parameters based on a Sample’s Statistics?
- 12. • This can be done with a measure of reliability called the confidence level, which is the proportion of times that an estimating procedure will be correct. • Or the significance level, which measures how frequently the conclusion will be wrong in the long run. 4/3/2023 12
- 13. Types of Data and Information • A variable is some characteristic of a population or a sample. • The values of the variable are the possible observations of the variable. • Data are the observed values of a variable. 4/3/2023 13
- 14. Types of Data Data Qualitative • Ordinal • Nominal Quantitative • Interval • Ratio 4/3/2023 14
- 15. Types of Data and Information Nominal Data ( also called categorical or qualitative) Such as marital status, gender,...... We often record nominal data by arbitrarily assigning a number to each category (codes) to store this type of data. Male 1 Female 2 4/3/2023 15
- 16. Interval data ( quantitative or numerical) Are real numbers, such as weights, heights, and incomes. Ordinal Data appear to be nominal, but their numerical codes are in order. Because the codes are arbitrarily assigned, we cannot calculate and interpret the differences. When assigning codes to the values, we can use any set of codes , but we should maintain the order of the values. 4/3/2023 16
- 17. Examples of Ordinal data • Degree of illness: none, mild, moderate, acute, chronic. • Opinion of students about Stat. classes: Very unhappy, unhappy, neutral, happy, Very happy. 4/3/2023 17
- 18. Calculations for Types of Data Interval Data :values are real numbers, all calculations are valid. Ordinal data : The only permissible calculations are ones involving the ranking process . Nominal Data : values are the arbitrary numbers that represent categories to be used to store data. Only calculations based on the frequencies of occurrence are valid( to count the occurrence of each category). 4/3/2023 18
- 19. Hierarchy of Data • The data types can be placed in order of the permissible calculations. Higher-level data may be treated as lower-level ones, but not the vice versa. Interval data Ordinal data Nominal data 4/3/2023 19
- 20. Types of Variables • The variables whose observations constitute our data will be given the same name as the type of data. 4/3/2023 20
- 21. Types of Numerical Data There are 2 forms of numerical data: 1.Discrete Data 2.Continuous Data Copyright © 2010 Pearson Addison-Wesley. All rights reserved. 1 - 21
- 22. Discrete Data Information that is collected by counting is called discrete data. The data are collected by counting exact amounts and you list the information or values. e.g. the number of children in a family; the number of children with birthdays in January; the number of goals scored at a soccer match. Copyright © 2010 Pearson Addison-Wesley. All rights reserved. 1 - 22
- 23. Continuous Data Continuous data values form part of a continuous scale and the values can not all be listed, e.g. The mass of a baby at birth is continuous data, as there is no reason why a baby should not have a mass of 3,25167312 kg – even if there is no scale that could measure so many decimal places. Copyright © 2010 Pearson Addison-Wesley. All rights reserved. 1 - 23