BUS 220: Elementary Statistics

Slides:



Advertisements
Similar presentations
Measures of Location and Dispersion
Advertisements

THE ARITHMETIC MEAN The arithmetic mean is the statistician’s term for what the layman knows as the average. It can be thought of as that value of the.
Copyright © 2014 by McGraw-Hill Higher Education. All rights reserved.
Describing Data: Measures of Dispersion
Describing Data: Measures of Central Tendency
BUS 220: ELEMENTARY STATISTICS
BUS 220: ELEMENTARY STATISTICS
DESCRIPTIVE STATISTICS
1 1 Slide © 2003 South-Western/Thomson Learning TM Slides Prepared by JOHN S. LOUCKS St. Edwards University.
1 1 Slide © 2014 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole.
Basic Statistics Measures of Central Tendency.
Lecture 2 Part a: Numerical Measures
Chapter Three McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved
Math Qualification from Cambridge University
Chap 3-1 EF 507 QUANTITATIVE METHODS FOR ECONOMICS AND FINANCE FALL 2008 Chapter 3 Describing Data: Numerical.
Descriptive Statistics – Central Tendency & Variability Chapter 3 (Part 2) MSIS 111 Prof. Nick Dedeke.
B a c kn e x t h o m e Parameters and Statistics statistic A statistic is a descriptive measure computed from a sample of data. parameter A parameter is.
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Ch. 2-1 Statistics for Business and Economics 7 th Edition Chapter 2 Describing Data:
Chapters 3 & 4 Alan D. Smith Descriptive Statistics -
Ka-fu Wong © 2004 ECON1003: Analysis of Economic Data Lesson2-1 Lesson 2: Descriptive Statistics.
Intro to Descriptive Statistics
Slides by JOHN LOUCKS St. Edward’s University.
Describing Data: Numerical Measures
Chap 3-1 Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chapter 3 Describing Data: Numerical Statistics for Business and Economics.
Describing Data: Numerical Measures
Describing Data Measures of Location Goals
Describing Data: Numerical Measures
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Describing Data: Numerical Measures Chapter 3.
Describing Data: Numerical
Describing Data: Numerical Measures Chapter 3 McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
CHAPTER 3 : DESCRIPTIVE STATISTIC : NUMERICAL MEASURES (STATISTICS)
Chapter 3 – Descriptive Statistics
Introduction and Descriptive Statistics
JDS Special Program: Pre-training1 Basic Statistics 01 Describing Data.
Describing Data: Numerical Measures Chapter 3 McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
Describing Data: Numerical Measures Chapter 03 McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved.
4 - 1 Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights reserved.
Describing Data: Numerical Measures. GOALS 1.Calculate the arithmetic mean, weighted mean, median, mode, and geometric mean. 2.Explain the characteristics,
Chapter Three McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved
Business Statistics Spring 2005 Summarizing and Describing Numerical Data.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Describing Data: Numerical Measures Chapter 3.
Chapter 3: Central Tendency. Central Tendency In general terms, central tendency is a statistical measure that determines a single value that accurately.
Chapter Three McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved. Describing Data: Numerical Measures.
Business Statistics, 4e, by Ken Black. © 2003 John Wiley & Sons. 3-1 Business Statistics, 4e by Ken Black Chapter 3 Descriptive Statistics.
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall2(2)-1 Chapter 2: Displaying and Summarizing Data Part 2: Descriptive Statistics.
Describing Data: Numerical Measures Chapter 3 McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.
Chapter Three McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved.
Chapter 3 Descriptive Statistics: Numerical Methods.
Describing Data: Numerical Measures Chapter 03 Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin.
Day 2. GOALS 1.Calculate the arithmetic mean, weighted mean, median, mode, and geometric mean. 2.Explain the characteristics, uses, advantages, and disadvantages.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Describing Data: Numerical Measures Chapter 3.
Describing Data: Numerical Measures Chapter 3 McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.
Describing Data: Numerical Measures
Statistics for Business
Chapter 3 Describing Data Basic Statistics for Business and Economics
Topic 3: Measures of central tendency, dispersion and shape
Introduction and Descriptive Statistics
Chapter 3 Created by Bethany Stubbe and Stephan Kogitz.
Descriptive Statistics
Characteristics of the Mean
MEASURES OF CENTRAL TENDENCY
Describing Data: Numerical Measures
BUS7010 Quant Prep Statistics in Business and Economics
Describing Data: Numerical Measures
Describing Data: Numerical Measures
Describing Data: Numerical Measures
Describing Data: Numerical Measures
Describing Data: Numerical Measures
Presentation transcript:

BUS 220: Elementary Statistics Chapter 3: Numerical Measures

Chapter 3: GOALS Calculate the measures of central tendency including arithmetic mean, weighted mean, median, mode, and geometric mean. Understand the advantages and disadvantages of those measures. Identify whether a distribution is skewed or symmetric by looking at the positions of mean, median and mode. 3/28/2017

Chapter 3: GOALS… Calculate the measures of dispersion including range, mean deviation, variance, and standard deviation. Understand the characteristics, advantages, and disadvantages of those measures. Understand the Chebshev’s theorem and the empirical rule as they are applied to a set of observation. 3/28/2017

Numerical Descriptive Measures Measures of central tendency Arithmetic Mean Weighted Mean Median Mode Geometric Mean Measures of Dispersion Range Mean Deviation Variance Standard Deviation 3/28/2017

Arithmetic Mean For ungrouped data, the population/sample arithmetic mean is the sum of all the population/sample values divided by the total number of values: population mean sample mean 3/28/2017

EXAMPLE – Population Mean 3/28/2017

EXAMPLE – Sample Mean 3/28/2017

Properties of the Arithmetic Mean Every set of interval-level and ratio-level data has a mean. All the values are included in computing the mean. The mean is unique. The sum of the deviations of each value from the mean is zero. 3/28/2017

Weighted Mean The weighted mean of a set of numbers X1, X2, ..., Xn, with corresponding weights w1, w2, ...,wn, is computed from the following formula: 3/28/2017

EXAMPLE – Weighted Mean The Carter Construction Company pays its hourly employees $16.50, $19.00, or $25.00 per hour. There are 26 hourly employees, 14 of which are paid at the $16.50 rate, 10 at the $19.00 rate, and 2 at the $25.00 rate. What is the mean hourly rate paid the 26 employees? 3/28/2017

The Median The Median is the midpoint of the values after they have been ordered from the smallest to the largest. There are as many values above the median as below it in the data array. For an even set of values, the median will be the arithmetic average of the two middle numbers. 3/28/2017

EXAMPLES - Median The ages for a sample of five college students are: 21, 25, 19, 20, 22 Arranging the data in ascending order gives: 19, 20, 21, 22, 25. Thus the median is 21. The heights of four basketball players, in inches, are: 76, 73, 80, 75 Arranging the data in ascending order gives: 73, 75, 76, 80. Thus the median is 75.5 3/28/2017

Properties of the Median It is not affected by extremely large or small values and is therefore a valuable measure of central tendency when such values occur. It can be computed for ratio-level, interval-level, and ordinal-level data. It can be computed for an open-ended frequency distribution if the median does not lie in an open-ended class. 3/28/2017

The Mode The mode is the value of the observation that appears most frequently. 3/28/2017 BUSA320/Sophea Chea

Example - Mode 3/28/2017

The Geometric Mean Useful in finding the average change of percentages, ratios, indexes, or growth rates over time. Has a wide application in business and economics in finding the percentage changes in sales, salaries, or economic figures, such as the GDP and interest rate which compound or build on each other. Will always be less than or equal to the arithmetic mean. 3/28/2017

EXAMPLE – Geometric Mean The return on investment earned by Atkins construction Company for four successive years was: 30, 20, -40, and 200 percent. The geometric mean rate of return on investment is: 3/28/2017

Dispersion: Why Study Dispersion? Mean or the median, only describes the center of the data, but it does not tell us anything about the spread of the data. For example, if your nature guide told you that the river ahead averaged 3 feet in depth, would you want to wade across on foot without additional information? Probably not. You would want to know something about the variation in the depth. A second reason for studying the dispersion in a set of data is to compare the spread in two or more distributions. 3/28/2017

Samples of Dispersions 3/28/2017

Measures of Dispersion Range Mean Deviation Variance and Standard Deviation 3/28/2017

EXAMPLE – Range Range = Largest – Smallest value = 80 – 20 = 60 The number of cappuccinos sold at the Starbucks location in the Orange Country Airport between 4 and 7 p.m. for a sample of 5 days last year were 20, 40, 50, 60, and 80. Determine the range for the number of cappuccinos sold. Range = Largest – Smallest value = 80 – 20 = 60 3/28/2017

EXAMPLE – Mean Deviation Determine the mean deviation for the number of cappuccinos sold. 3/28/2017 BUSA320/Sophea Chea

Exercise 38—return on investment of 8 companies 10.6 12.6 14.8 18.2 12.0 12.2 15.6 Range 18.2-10.6=7.6% Arithmetic mean 13.85% Mean deviation 2.0% Interpret the results: The ROI or the eight companies ranges from 10.6 to 18.2 which is 7.6% in range. On the average the return on investment deviates 2% from the mean of 13.85%. 3/28/2017 BUSA320/Sophea Chea

EXAMPLE – Variance and Standard Deviation The number of traffic citations issued during the last five months in Beaufort County, South Carolina, are 38, 26, 13, 41, and 22. What is the population variance? 3/28/2017

EXAMPLE – Sample Variance The hourly wages for a sample of part-time employees at Home Depot are: $12, $20, $16, $18, and $19. What is the sample variance? 3/28/2017 BUSA320/Sophea Chea

Using Excel for Descriptive Statistics Table 2–4 in Chapter 2 shows the prices of the 80 vehicles sold last month at Whitner Autoplex in Raytown, Missouri. Determine the mean and the median selling price. The mean and the median selling prices are reported in the following Excel output. There are 80 vehicles in the study. So the calculations with a calculator would be tedious and prone to error. 3/28/2017 BUSA320/Sophea Chea

Read the lecture note on how to activate the analysis ToolPak for Excel 3/28/2017

The Relative Positions of the Mean, Median and the Mode 3/28/2017 BUSA320/Sophea Chea

Real Estate Data from Jacksonville, FL 3/28/2017 BUSA320/Sophea Chea

Real Estate Data from Jacksonville, FL 3/28/2017 BUSA320/Sophea Chea

Application of Standard Deviation Because it is standardized it is meaningful to use standard deviation to compare between two samples E.g. two samples of productions rate at two plants has approximately the same mean, how if one has std deviation of 10 and another is 7 we can conclude that the first plant has more disperse rate of productions 3/28/2017 BUSA320/Sophea Chea

Application of Standard Deviation: Chebyshev’s Theorem For any set of observations (sample or population), the proportion (percentage) of the values that lie within k standard deviations of the mean is at least 1 – 1/k2 percent. where k is any constant greater than 1 3/28/2017 BUSA320/Sophea Chea

Chebyshev’s Theorem The arithmetic mean biweekly amount contributed by the Dupree Paint employees to the company’s profit-sharing plan is $51.54, and the standard deviation is $7.51. At least what percent of the distributions lie within plus 3.5 standard deviations and minus 3.5 standard deviations of the mean? 3/28/2017

Application of Standard Deviation: The Empirical Rule 3/28/2017 BUSA320/Sophea Chea