Chapter 1 Introduction to Statistics 1-1 Overview 1-2 Types of Data 1-3 Critical Thinking 1-4 Design of Experiments.

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Chapter 1 Introduction to Statistics 1-1 Overview 1-2 Types of Data 1-3 Critical Thinking 1-4 Design of Experiments

Section 1-1 Overview

Overview A common goal of studies and surveys and other data collecting tools is to collect data from a small part of a larger group so we can learn something about the larger group. In this section we will look at some of the ways to describe data.

Definitions  Data: observations (such as measurements, genders, survey responses) that have been collected  Statistics:a collection of methods for planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data population parameter

 Population : the complete collection of all elements (scores, people, measurements, and so on) to be studied; the collection is complete in the sense that it includes all subjects to be studied  Census: Collection of data from every member of a population  Sample: Sub collection of members selected from a population

Chapter Key Concepts  Sample data must be collected in an appropriate way, such as through a process of random selection.  If sample data are not collected in an appropriate way, the data may be so completely useless that no amount of statistical torturing can salvage them.

Section 1-2 Types of Data

Key Concept The subject of statistics is largely about using sample data to make inferences (or generalizations) about an entire population. It is essential to know and understand the definitions that follow.

 Parameter:a numerical measurement describing some characteristic of a population.  Statistic:a numerical measurement describing some characteristic of a sample.  Quantitative data: numbers representing counts or measurements.Example: The weights of supermodels  Qualitative (or categorical or attribute) data …can be separated into different categories that are distinguished by some nonnumeric characteristic.Example: The genders (male/female) of professional athletes sample statistic

Working with Quantitative Data Quantitative data can further be described by distinguishing between discrete and continuous types.

 Discrete data result when the number of possible values is either a finite number or a ‘countable’ number (i.e. the number of possible values is 0, 1, 2, 3,..) Example: The number of eggs that a hen lays  Continuous (numerical) data result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps Example: The amount of milk that a cow produces; e.g gallons per day

4 Levels of Measurement: another way to classify data  Nominal level of measurement:characterized by data that consist of names, labels, or categories only, and the data cannot be arranged in an ordering scheme (such as low to high) Example: survey responses yes, no, undecided  Ordinal level of measurement involves data that can be arranged in some order, but differences between data values either cannot be determined or are meaningless Example: Course grades A, B, C, D, F  Interval level of measurement: like the ordinal level, with the additional property that the difference between any two data values is meaningful, however, there is no natural zero starting point (where none of the quantity is present) Example: Years 1000, 2000, 1776, and 1492  Ratio level of measurement: the interval level with the additional property that there is also a natural zero starting point (where zero indicates that none of the quantity is present); for values at this level, differences and ratios are meaningful Example: Prices of college textbooks ($0 represents no cost)

Summary - Levels of Measurement  Nominal - categories only  Ordinal - categories with some order  Interval - differences but no natural starting point  Ratio - differences and a natural starting point

Recap  Basic definitions and terms describing data  Parameters versus statistics  Types of data (quantitative and qualitative)  Levels of measurement In this section we have looked at:

Class Survey Please complete the survey and submit. Do not sign your name. 1)___Female ___Male 2)Randomly select four digits and enter them here:__ __ __ __ 3)Your eye color: 4)Your height in inches: 5)Total value of the coins now in your possession: 6)Number of keys in your possession right now: 7)Number of credit cards in your possession right now: 8)Enter the last four digits of your social security number: ___ ___ ___ ___ 9)Record your pulse rate by counting the number of heartbeats for one minute. 10)Do you exercise vigorously for at least 20 minutes twice a week (running, swimming, cycling, tennis, basketball, etc.)? YES/NO 11)How many classes are you taking this semester? 12)Are you currently employed? YES/NO If yes, how many hours do you work each week? 13) During the past 12 months, have you been the driver of a car that was involved in a crash? YES/NO 14) Do you smoke? YES/NO 15) Are you: Left Handed Right-handedAmbidextrous