MM150 Unit 8 Seminar. Definitions Statistics - The art and science of gathering, analyizing, and making predictions from numerical information obtained.

Slides:



Advertisements
Similar presentations
SAMPLING METHODS OR TECHNIQUES
Advertisements

Chapter 13 Section 1 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Probability & Statistics
Lesson Designing Samples. Knowledge Objectives Define population and sample. Explain how sampling differs from a census. Explain what is meant by.
The Where, Why, and How of Data Collection
Categories of Sampling Techniques n Statistical ( Probability ) Sampling: –Simple Random Sampling –Stratified Random Sampling –Cluster Random Sampling.
Introduction to Statistics
Statistical Methods Descriptive Statistics Inferential Statistics Collecting and describing data. Making decisions based on sample data.
SECTION 12-1 Visual Displays of Data Slide
Statistics Statistics is the art and science of gathering, analyzing, and making inferences (predictions) from numerical information, data, obtained in.
MATH1342 S08 – 7:00A-8:15A T/R BB218 SPRING 2014 Daryl Rupp.
Slide Copyright © 2009 Pearson Education, Inc. Slide Copyright © 2009 Pearson Education, Inc. Welcome to Survey of Mathematics! Unit 8 –
Chapter 13 Statistics © 2008 Pearson Addison-Wesley. All rights reserved.
What You Will Learn Frequency Distributions Histograms
© 2008 Pearson Addison-Wesley. All rights reserved Chapter 1 Section 13-1 Visual Displays of Data.
12.1 – Visual Displays of Data In statistics: A population includes all of the items of interest. A sample includes some of the items in the population.
Thinking Mathematically
Chapter 13 Section 3 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Intro Stats Lesson 1.3 B Objectives: SSBAT classify different ways to collect data. SSBAT distinguish between different sampling techniques. Standards:
Chapter 13 Section 1 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Chapter 1 DATA AND PROBLEM SOLVING. Section 1.1 GETTING STARTED.
STAT 211 – 019 Dan Piett West Virginia University Lecture 1.
Section 14.1 Organizing and Visualizing Data. Objectives 1. Describe the population whose properties are to be analyzed. 2. Organize and present data.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Prob and Stats, Aug 26 Unit 1 Review - Fundamental Terms and Definitions Book Sections: N/A Essential Questions: What are the building blocks of Statistics,
1 Left mouse click and hold. Drag to the right to enlarge the pod. To maximize chat, minimize roster by clicking here To resize your pods: Place your mouse.
Slide 1 Copyright © 2004 Pearson Education, Inc. Misuses of Statistics  Bad Samples  Small Samples  Misleading Graphs  Pictographs  Distorted Percentages.
MM150 Unit 8 Seminar Statistics. 8.1 Sampling Techniques 2.
SAMPLING TECHNIQUES. Definitions Statistical inference: is a conclusion concerning a population of observations (or units) made on the bases of the results.
An Overview of Statistics Section 1.1. Ch1 Larson/Farber 2 Statistics is the science of collecting, organizing, analyzing, and interpreting data in order.
MM150 Unit 8 Seminar. Probability (Unit 7) Statistics (Unit 8) : Gathering data; organizing data Statistics (Unit 9) : Analyzing data; making conclusions.
Understanding Basic Statistics Chapter One Organizing Data.
 The mean is typically what is meant by the word “average.” The mean is perhaps the most common measure of central tendency.  The sample mean is written.
Notes 1.3 (Part 1) An Overview of Statistics. What you will learn 1. How to design a statistical study 2. How to collect data by taking a census, using.
MATH104 Chapter 12 Statistics 12.1 Intro Sampling, Frequency Distributions, and Graphs Terms: · Descriptive statistics · Inferential statistics.
+ Chapter 1. + Chapter 1 Section 1: Overview of Statistics.
9.1 – Visual Displays of Data Objective – TSW construct visual displays of data. Chapter 1.
Slide Copyright © 2009 Pearson Education, Inc. Slide Copyright © 2009 Pearson Education, Inc. Welcome to Unit 8! Statistics.
Slide Copyright © 2009 Pearson Education, Inc. Slide Copyright © 2009 Pearson Education, Inc. Chapter 8 Statistics.
Elementary Statistics (Math 145) June 19, Statistics is the science of collecting, analyzing, interpreting, and presenting data. is the science.
 2012 Pearson Education, Inc. Slide Chapter 12 Statistics.
Unit 8: Statistics Prof. Carolyn Dupee July 3, 2012.
MATH 201: STATISTICS Chapters 1 & 2 : Elements of Statistics
Chapter 12 Statistics 2012 Pearson Education, Inc.
Chapter 12 Statistics.
Probability and Statistics
Math 145 January 23, 2007.
CONSTRUCTION OF A FREQUENCY DISTRIBUTION
7-1 Statistics Sampling Techniques.
Graphs.
Introduction to Statistics
Gathering and Organizing Data
THE STAGES FOR STATISTICAL THINKING ARE:
10.2 Statistics Part 1.
Definitions Covered Statistics Individual Variable
Week 3 Lecture Statistics For Decision Making
STAT 145.
Probability and Statistics
THE STAGES FOR STATISTICAL THINKING ARE:
Drill Put these numbers in order from least to greatest: {-2, 6, 3, 0, -5, 1, -8, 8} b) Add the #’s together.
STAT 245.
Constructing and Interpreting Visual Displays of Data
Gathering and Organizing Data
Experimental Design Experiments Observational Studies
Math 145 September 6, 2005.
Math 145 September 5, 2007.
Section 13.1 Sampling Techniques
Graphs.
Sampling Techniques Statistics.
EQ: What is a “random sample”?
Presentation transcript:

MM150 Unit 8 Seminar

Definitions Statistics - The art and science of gathering, analyizing, and making predictions from numerical information obtained from an experiment. Data - The numerical information obtained. Descriptive Stats - Concerned with the collection, organization, and analysis of data. Inferential Stats - Concerned with making generalizations or predictions of the data.

Population - All items or people of interest. Sample - A subset of the population.

Experiment A jar with 90 blue marbles and 10 red marbles

Random Sampling - Each item in the population has an equal chance of being selected. The best time to use random sampling is when all items in the population are similar with regard to the characteristic we are concerned with (ie. different colored golf balls) Best practices: Use a random number generator or a table of random numbers.

Systematic Sampling - obtaining a sample by drawing every nth item with the first item determined by a random number. What to watch for: (1) The list from which the systematic sampling is taken must contain the entire population. (2) The population is comprised of items where every nth item is made/inspected by the same entity.

Cluster Sampling - A random selection of groups of units. Also called an area sample because it can be based on geography.

Stratified Sampling - A population is divided into parts, called strata, to make sure each stratum is selected from. Some knowledge of the population is needed to complete this type of sampling.

Convenience Sampling - Using data that is easy obtained. Things to consider: (1) May be only information available (2) Limited info is better than none (3) Can be extremely biased

Frequency Distribution A listing of the observed values and the corresponding frequency of occurrence of each value.

Frequency Distribution Example Twelve students recored the number of siblings they have. 0, 1, 2, 3, 1, 1, 0, 3, 2, 2, 1, 0 Number of Siblings Frequency Note: = 12

Rules for Data Groups By Classes (1) The classes should be of the same “width.” (2) The classes should not overlap. (3) Each piece of data should belong to only one class. *A frequency distribution should be constructed with classes.

Frequency Distribution with Classes A professor wants to construct a frequency distribution for end-of-term grades. We must determine upper and lower class limits. One way that makes sense is Lower Class Limits Upper Class Limits Class Width is 10. In 90-99, there are 10 data scores: 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 Subtract Consecutive Upper Class Limits: = 10 Subtract Consecutive Lower Class Limits: = 10

Circle Graph Example 32 people are interviewed to determine their favorite movie genre. Below are the results. 9 Action 16 Comedy 7 Drama To construct the circle graph, we must find the measure of the central angle for each section of the circle graph. The circle will be divided into 3 sections.

Circle Graph Con’t Genre No. of People Percent of Total Measure of Central Ang Action9 9/32 * 100 = 28.12% * 360 = Comedy16 16/32 * 100 = 50%0.5 * 360 = 180 Drama7 7/32 * 100 = 21.87% * 360 = 78.77

Circle Graph Con’t Comedy ActionDrama

Stem and Leaf Plot Example Construct a stem and leaf plot for the following data scores: 98, 85, 99, 78, 81, 77, 90, 74, 72, 81, 88, 92, | 1 represents 81