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by: YALIN ZHANG

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# MAS 201 Chapter 1-2 MAS 211

Marketplace > University of Miami > Business > MAS 211 > MAS 201 Chapter 1 2
YALIN ZHANG
UM
Mary McKenry

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MAS 201 class note. Especially for the students who are taking Professor Mary Mckenry's class
COURSE
PROF.
Mary McKenry
TYPE
Class Notes
PAGES
10
WORDS
KARMA
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## Popular in INTRODUCTION TO BUSINESS STATISTICS

This 10 page Class Notes was uploaded by YALIN ZHANG on Monday February 2, 2015. The Class Notes belongs to MAS 211 at University of Miami taught by Mary McKenry in Winter2015. Since its upload, it has received 330 views. For similar materials see INTRODUCTION TO BUSINESS STATISTICS in Business at University of Miami.

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Date Created: 02/02/15
CHAPTER 1 SUMMARY MAS 201 1 Population vs Sample Population is the collection of all units under study Sample is a subset of the population used for analysis 2 Parameter vs Statistic A parameter is a measure which describes the population A statistic is a measure which describes the sample 3 Descriptive Statistics vs inferential Statistics Descriptive statistics are the collection of methodologies used to describe a set of data lnferential statistics are methodologies used to make an inference about a population based on the sample 4 Primary Sources vs Secondary Sources Data is considered as obtained from a primary source when the actual raw data is obtained from the originatin 7 s I e eg surveys experiments corporate recordsffg w Data is considered as being obtained from a secondary source when the data has been com 39Ied b a third party eg government publications syndicated services such as the ielsen ratings 5 Types of Date a Categorical special case are binary variables b Numerical i Discrete takes on only whole numbers ii Continuous between any two values there is another value 5 Levels of measurement mgr mg a Nominal namenmmo laest V Iz 39 ampw 39 W b Ordinal quotorderingquot nature celery Wurler c interval quotnumeric and the number has meaningquot d Rationnumericl number has meaning and a true zero 7 1 Mary McKenry Ml I MAS 201 Canned byCamScanner 7 8 Census vs Sample a Census b Sample c Why sample i More expedient ii Less costly iii More efficient Sampling Methods a b C Frame listing of all entities comprising the population Nonprobability Samples Probability Samples Survey Errors i Coverage ErrorSelection bias exclusion from the frame ii Nonresponse Error respondents not willing to answer iii Sampling Error difference between sample and population iv Measurement Error inaccuracies in the recorded responses Scanned by CamScanner Id 2 1 WEQn PWVlL l noquot S1T CL H Jmml gucghtmw d0 W femwg f iquot I Di Scra CamPFW 6h hmmbkz39n I A U 01 bug AQro 4T 14 Scanned by CamScanner elm 2 all VM39Q 39 39 39 3 9mm 3 WWW 7 7 Ifme M x mm w 55 7 lrl ihwj dz hxl39bn 51 7 a 7 7 U W In lkswm SmeM 35 Pagen w i J 5 Infare nl SMXIEL 2 W L m w xggtr5nwm 2 if W I 32o w 39 Sam 3 A gm 0 W 5 it d 57 Cum ch 1L FEW 04 quot 5 Ma a th Cw e 39 ml x3 mmma th 39 V vH JL 7 m1 E CF Mmme whf K7 a 7 v u f 1 1 W 1quot 396 Mquot C W g cf 7 6 V r i 39 a v My 973 Comma l I 111 iquot 939 MN MW lamber lm S E W 133 Scanned by CamScanner Chapter 2 Presenting Data in Tables and Charts Numerical Data Stem a fDia ram 39 o Break up number into stem and leaf and place on diagram 0 Create second diagram where leaf portions are in numeric order Example The PIE ratios for 30 stocks traded on the NYSE were Mary McKenry MAS 201 I Scanned by CamScanner 0 Tables and Charts for numerical Data 0 Frequency Distribution Groups must be EXAMPLE The data below represent the electricity cost during July 2002 96 157 141 95 108 171 185 149 163 119 Curren Mmg r ap Mutually Exclusive Exhaustive of Groups Between 5 and 15 Approximate width of groups Class Boundaries 0 Relative Frequency Distribution Proportion Percentage Percentage Distribution 0 Cumulative Distribution Cumulative Frequency Distribution Cumulative Percentage Distribution 202 90 206 150 183 178 116 175 154 151 147 172 123 130 114 102 111 128 143 135 153 148 144 187 191 40 53 Scanned by CamScanner 197 213 166 166 1 37 Width e Rangerl Desired of groupings 127 130 109 139 129 66 17 0 Percentage Distribution er 0 Cumulative Frequency Distribution 0 Cumulative Percentage Distribution f d 3A 21 C it 30 7 4 002 lt97 450 M 31 1W 7 may quottquot quotn 7 2351 126 a g 911 Mg 31 20 Hr tiLl to VG 139 L126 ti0 6 n o If 11 9391 0 idem 539 0 3 Q7 0697 73727 Ti H4 5 5 root 1 57 Ma ryFllElche ry I 00 MAS 201 a 165 167 149 158 Using class intervals 8099 100 119 120139 etc construct Frequency Distribution 111 quot 9 20quot r l 991 395 quot 4quot 4 A an y 39 1 39 quotA 2 A A A x A quotJw l ayir its 5 F 91 tA 33 quot f 413 v a 39 39 j quot v 39 4 39 If 1 1w yttri 3d I39m i ccwfgq t h 39 l 39lt I 39 minatmiaiheu bgr39g t m rE ili hll el Representation of Frequency Distributions 0 Histogram graphical representation of the freq 0 Frequency Polygon and Percentage Polygon u 0 Ogive a Cumulative Percentage Polygon uses uppe uency distribution ses midpoints r bound Using the same Example Construct 0 Histogram rectangles should 0 Frequency Polygon and Percen o Ogive r cf or UL have equal width I tage Polygon same except yaxus it 20 aquot 3 7M 111 frHc 1mm vim59 7 M 2v Hus t 56 Wall3 quot M 39 a 939 quota 3 139 f 21 224 f a F rEDliz larylTt en r39y go W MASZO I 3 Scanned by CamScanner Bivariate Tables and Graphs y byes Crosstabulation Tables tabular summary of data for two varla Example p 61 48 A study of job satisfaction was conducted fo r four occupations Job O satisfaction was measured using an 18item questionnaire With each questlon receiving a response score of 1 to 5 with higher scores indicating greater f satisfaction The sum of the 18 scores provides the job satisfaction score for each individual in the sample The data are as follows Occupation Score Occupation Score Occupation Score Lawyer 42 Physical Therapist 78 Systems Analyst 6039 PhYSical Therapist 86 Systems Analyst 44 Physical Therapist 59 Lawyer 42 Systems Analyst 71 Cabinetmaker 78 Systems Analyst 55 Lawyer 50 Physical Therapist 60 Lawyer 38 Lawyer 46 Physical Therapist 50 Cabinetmaker 79 Cabinetmaker 69 Cabinetmaker 79 Lawyer 44 Physical Therapist 60 Systems Analyst 62 Systems Analyst 41 Systems Analyst 64 Lawyer 45 Physical Therapist 55 Physical Therapist 55 Cabinetmaker 84 Systems Analyst 66 Cabinetmaker 64 Physical Therapist 62 Lawyer 53 Cabinetmaker 59 Systems Analyst 73 Cabinetmaker 65 Cabinetmaker 54 Cabinetmaker 60 Lawyer 74 Systems Analyst 76 Lawyer 64 PhysicalTherapist 52 a Construct a crosstabulation of occupation and job satisfaction score 3333 CateC Sn w4 7 ewes 7H2 as wheels I 833693 Ambrt b What observations can you make concerning the level of job satisfaction for these occupations Mary McKenry MAS 201 4 Scanned by CamScanner 39 Scatter dia o Loolgilnagn Eelgart rlt Isgescgbing two numerical variables Positive P etween the two variables 39 Negative 0 Linear Quadratic o If one variable is conside 39 the yams 9 dependent It should be graphed along 0 Care shodld be given to the scale Easy to distort strength of relationship by changing scale EXAMPLE The following data represent the number of calories and the percentage of fat per half cup serving of 1 chocolate ice creams Calories 270 150 170 140 160 150 160 290 170 190 Fat 18 8 10 8 9 9 9 17 9 10 Calories 190 160 170 150 150 110 180 g Fat 10 8 9 8 8 3 9 a 31k y I irh a if L Graph a scatter diagram where Calories may be considered Qgi gzni 0n Fat content aftth f Lavagequot3 392 39 l i to 3quotquot o Mary McKenw MAS 201 S Scanned by CamScanner Tables and Charts for Categorical Data 0 Summary table 0 Presents the frequency distribution for Categorical Data 0 Usually includes Percentages 0 Graphs 0 Bar Charts Used to compare categories Vertical or Horizontal Frequencies or Percentages o Pie Chart Used to display proportion of the whole with an attribute Based on the proportion of 36000 of the entire circle 0 Pareto Diagram I Often used in Quality Improvement I Used to separate the vital few from the trivial many Combines the vertical bar chart with a cumulative polygon Example In a Wall Street Journal article Stepan Yokich president of the UAW denounced GM s trend of moving jobs outside unionized GM factories to non union partsmaking factories The article noted that the UAW had 770000 members including 220000 at GM 101000 at Ford Motor and75000 at Daimler Chrysler a Construct a frequency and percentage summary table for UAW workers Use four categories one for each of three Detroit automakers and one for all other workers b Make a bar chart that depicts where members of the UAW work c Make a pie chart that depicts where members of the UAW work Scanned by CamScanner

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