Stat 101Dr SaMeH1 Statistics (Stat 101) Associate Professor of Environmental Eng. Civil Engineering Department Engineering College Almajma’ah University /2011 Sameh Saadeldin Ahmed

Stat 101Dr SaMeH2 Chapter 1 WeekSubjectContent 1 st week Concepts of Probability and Statistics What is Statistics? Types of Statistics Basic Terms Types of Variables Sources of Data Data Collection Approaches

Stat 101Dr SaMeH3 The study of statistics has become more popular than ever over the past four decades. The increasing availability of computer and statistics software packages has enlarged the role of statistics as a tool for empirical research. As a result, statistics is used in almost all professions, from medicine to sports. 1.0Introduction

Stat 101Dr SaMeH4 1.1What is Statistics? Statistics is a group of methods used to collect, analyze, present and interpret data and to make decisions. Statistics has two aspects: Theoretical or mathematical statistics : deals with the development, derivation, and proof of statistical theorems, formulas, rules and laws. Applied statistics : involves the applications of those theorems, formulas, rules and laws to solve real-world problems.

Stat 101Dr SaMeH5 1.2Types of Statistics 1.2.1Descriptive Statistics: Descriptive statistics consists of methods for organizing, displaying, and describing data by using tables, graphs and summary measures Inferential Statistics: Inferential statistics consists of methods that use the sample results to help make decisions or predictions about a population.

Stat 101Dr SaMeH6 Probability, which gives a measurement of the likelihood that a certain outcome will occur, acts as a link between descriptive and inferential statistics. DescriptiveInferential Probability

Stat 101Dr SaMeH7 1.3Population versus Sample Ex: suppose a statistician is interested in knowing: The percentage of all voters in a college who will vote for a particular candidate in an election. The 1429 gross sales of all companies in Almajmaah city. Prices of all houses in Riyadh. Each of these groups is called the population for the respective example.

Stat 101Dr SaMeH8 Population or Target Population: A population consists of all elements – individuals, items, or objects – whose characteristics are being studied. The population that being studied is also called target population. Definition of Population Most of the time, decisions are made based on portions of populations.

Stat 101Dr SaMeH9 Example: the election polls conducted in United States to estimate the percentage of voters who favour various candidates in any presidential election are based on only a few hundred of a few thousand voters selected from across the country. In this case, the population consists of all registered voters in US. The sample is made up of the few hundred or few thousand voters who are included in an opinion poll. Thus, the collection of a few elements selected from a population is called a sample.

Stat 101Dr SaMeH10 Sample : A portion of the population selected for study is referred to as a sample. Definition of Sample Sample Population Population and sample

Stat 101Dr SaMeH11 Census and Sample Survey : A survey that includes every member of population is called census. The technique of collection information from a portion of the population is called a sample survey. Census and Representative sample Representative Sample : A sample that represents the characteristics of the population as closely as possible is called a representative sample.

Stat 101Dr SaMeH12 Example: to find the average income of families living in Riyadh city by conducting a sample survey, the sample must contain families who belong to different income groups in almost the same portion as they exist in the population. Such a sample is called representative sample.

Stat 101Dr SaMeH13 Random Sample: A sample drawn in such a way that each element of the population has a chance of being selected is called random sample. Random and Non-random Sampling with replacement and sampling without replacement..

Stat 101Dr SaMeH14 With and Without Replacement greenredblue

Stat 101Dr SaMeH15 Exercises 1.Briefly explain the terms: population, sample, representative sample, random sample, sampling with replacement and sampling without replacement. 2.Explain whether each of the following constitutes a population or a sample? Credit card debt of 100 families selected from a city Ages of all members of a family Amount spent on prescription drugs by 200 senior citizens in a large city. Scores of all students in statistics in statistics class.

Stat 101Dr SaMeH16 1.4Basic Terms This section explains the meaning of: an element, a variable, an observation, and a data set.

Stat 101Dr SaMeH17 Table 1.1: Students enrolment at six engineering departments DepartmentNo. of students Civil420 Mechanical140 Electrical330 Industrial50 Mining50 Chemical70 Variable Observation Element or Member

Stat 101Dr SaMeH18 Element or Member: An element or member of a sample or population is a specific subject or object (for example, a person, firm, item, state, or country) about which the information is collected. Element and Variable Variable A variable is a characteristic under study that assumes different values for different elements. In general, a variable assumes different values for different elements, as in table 1.1, for some elements in a data set; however, the value of the variable may be the same.

Stat 101Dr SaMeH19 Observation or Measurement: The value of a variable for an element is called observation. Observation and Data set Data Set A data set is a collection of observations on one or more variables.

Stat 101Dr SaMeH20 1.5Types of Variables A variable may be classifies as quantitative or qualitative: 1.5.1Quantitative Variables Example: incomes, heights, gross sales, prices of houses, number of accidents are examples of quantitative variables because each of them can be expressed numerically Qualitative Variables

Stat 101Dr SaMeH21 Quantitative Variable: A variable that can be measured numerically is called quantitative variable Quantitative Variable Quantitative variables classified to: discrete variables and continuous variables.

Stat 101Dr SaMeH22 Discrete Variable : A variable whose values are countable. Discrete Variable A discrete variable can assume only certain values with no intermediate values. Examples: The number of cars sold on any day at a car dealership is a discrete variable. (5, 6,…. Not 5.3!!). Number of people visiting a bank on any day. Number of cars in a parking area. Number of students in a class

Stat 101Dr SaMeH23 Continuous Variable : A variable that can assume any numerical value over a certain interval or intervals. Continuous Variable Some variables can not be counted, and they assume any numerical value between two numbers such variables are called continuous variables. Examples: The time taken to complete an examination (30 -60min.). Weight of people (kg, gm,..). Height of people (cm, mm,..) Note) any variable that involves money is considered a continuous variable.

Stat 101Dr SaMeH24 Qualitative Variable: A variable that can not assume a numerical value but can be classified into two or more nonnumeric categories is called qualitative variable Qualitative Variable Examples: Gender of person (M/F). Hair colour. The make of a car.

Stat 101Dr SaMeH25 1.5Types of Variables Types of variables Quantitative Qualitative Discrete Continuous

Stat 101Dr SaMeH26 1.6Cross-section versus Time-series Data 1.6.1Cross-section Data: Data collected on different elements at the same point in time or for the same period of time. Example: the information on incomes of 50 families for Time-series Data Data collected on the same element for the same variable at different points in time or for different period of time. Example: KSA exports for the years

Stat 101Dr SaMeH27 1.7Sources of Data Data may be obtained from 1. internal sources, 2. external sources, or 3.surveys and experiments

Stat 101Dr SaMeH28 1.8Summation Notation The following table lists four pairs of m and f values. Compute the following: a)  mb)  f 2 c)  m f d)  m 2 f m f591016

Stat 101Dr SaMeH29 End of Part 1 Get ready for a quiz (1)…… Next Lecture!!