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Elementary Statistics A Step by Step Approach Third Edition. 1-1. by Allan G. Bluman SLIDES PREPARED BY LLOYD R. JAISINGH MOREHEAD STATE UNIVERSITY MOREHEAD KY. Chapter 1. 1-2. The Nature of Probability and Statistics. WCB/McGraw-Hill. The McGraw-Hill Companies, Inc., 1998.

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slide1

Elementary Statistics

A Step by Step Approach

Third Edition

1-1

by

Allan G. Bluman

SLIDES PREPARED

BY

LLOYD R. JAISINGH

MOREHEAD STATE UNIVERSITY

MOREHEAD KY

chapter 1

Chapter 1

1-2

The Nature of Probability

and Statistics

WCB/McGraw-Hill

  • The McGraw-Hill Companies, Inc., 1998
outline
Outline

1-3

  • 1-1 Introduction
  • 1-2 Descriptive and Inferential Statistics
  • 1-3 Variables and Types of Data
  • 1-4 Data Collection and Sampling Techniques
outline4
Outline

1-4

  • 1-5 Computers and Calculators
objectives
Objectives

1-5

  • Demonstrate knowledge of all statistical terms.
  • Differentiate between the two branches of statistics.
  • Identify types of data.
objectives6
Objectives

1-6

  • Identify the measurement level for each variable.
  • Identify the four basic sampling techniques.
objectives7
Objectives

1-7

  • Explain the importance of computers and calculators in statistics.
1 1 introduction
1-1 Introduction

1-8

  • Statisticsconsists of conducting studies to collect, organize, summarize, analyze, and draw conclusions.
1 2 descriptive and inferential statistics
1-2 Descriptive and Inferential Statistics

1-9

  • Dataare the values (measurements or observations) that the variables can assume.
  • Variables whose values are determined by chance are called random variables.
1 2 descriptive and inferential statistics10
1-2 Descriptive and Inferential Statistics

1-10

  • A collection of data values forms a data set.
  • Each value in the data set is called a data value or a datum.
1 2 descriptive and inferential statistics11
1-2 Descriptive and Inferential Statistics

1-11

  • Descriptive statistics consists of the collection, organization, summation, and presentation of data.
1 2 descriptive and inferential statistics12
1-2 Descriptive and Inferential Statistics

1-12

  • A population consists of all subjects (human or otherwise) that are being studied.
  • A sampleis a subgroup of the population.
1 2 descriptive and inferential statistics13
1-2 Descriptive and Inferential Statistics

1-13

  • Inferential statistics consists of generalizing from samples to populations, performing hypothesis testing, determining relationships among variables, and making predictions.
1 3 variables and types of data
1-3 Variables and Types of Data

1-14

  • Qualitative variablesare variables that can be placed into distinct categories, according to some characteristic or attribute. For example, gender (male or female).
1 3 variables and types of data15
1-3 Variables and Types of Data

1-15

  • Quantitative variablesare numerical in nature and can be ordered or ranked. Example: age is numerical and the values can be ranked.
1 3 variables and types of data16
1-3 Variables and Types of Data

1-16

  • Discrete variablesassume values that can be counted.
  • Continuous variablescan assume all values between any two specific values. They are obtained by measuring.
1 3 variables and types of data17
1-3 Variables and Types of Data

1-17

  • Thenominal level of measurementclassifies data into mutually exclusive (nonoverlapping), exhausting categories in which no order or ranking can be imposed on the data.
1 3 variables and types of data18
1-3 Variables and Types of Data

1-18

  • Theordinal level of measurementclassifies data into categories that can be ranked; precise differences between the ranks do not exist.
1 3 variables and types of data19
1-3 Variables and Types of Data

1-19

  • Theinterval level of measurementranks data; precise differences between units of measure do exist; there is no meaningful zero.
1 3 variables and types of data20
1-3 Variables and Types of Data

1-20

  • Theratio level of measurementpossesses all the characteristics of interval measurement, and there exists a true zero. In addition, true ratios exist for the same variable.
1 4 data collection and sampling techniques
1-4 Data Collection and Sampling Techniques

1-21

  • Data can be collected in a variety of ways.
  • One of the most common methods is through the use of surveys.
  • Surveys can be done by using a variety of methods -
  • Examples are telephone, mail questionnaires, personal interviews, surveying records and direct observations.
1 4 data collection and sampling techniques22
1-4 Data Collection and Sampling Techniques

1-22

  • To obtain samples that are unbiased, statisticians use four methods of sampling.
  • Random samplesare selected by using chance methods or random numbers.
1 4 data collection and sampling techniques23
1-4 Data Collection and Sampling Techniques

1-23

  • Systematic samplesare obtained by numbering each value in the population and then selecting the kth value.
1 4 data collection and sampling techniques24
1-4 Data Collection and Sampling Techniques

1-24

  • Stratified samplesare selected by dividing the population into groups (strata) according to some characteristic and then taking samples from each group.
1 4 data collection and sampling techniques25
1-4 Data Collection and Sampling Techniques

1-25

  • Cluster samplesare selected by dividing the population into groups and then taking samples of the groups.
1 5 computers and calculators
1-5 Computers and Calculators

1-26

  • Computers and calculators make numerical computation easier.
  • Many statistical packages are available. One example is MINITAB. The TI-83 calculator can also be used to do statistical calculations.
  • Data must still be understood and interpreted.