MATHEMATICS-IIA. 1. Calculate the variance and standard deviation of the following continuous frequency distribution
|
|
- Bryce Potter
- 5 years ago
- Views:
Transcription
1 1. Calculate the variance and standard deviation of the following continuous frequency distribution d i = ( x i A ) c d i d i d i (A) d i = 15 d i = 105 Here =50, A=65, C=10, ( d i ) = 15, d i = 105 mean(x) = A + ( d i ) C = 65 + ( ) 10 = 65 3 = 6 Variance= C [( d i ) ( d i ) ] = [50(105) ( 15) ] = 100 [550 5] 500 = 1 [505] = 01 5 S.D= 01 = tutorial
2 . Calculate the variance and standard deviation of the following discrete frequency distribution x i x i x i (x i x) (x i x) (x i x) (x i x) = 1374 x i = 40 Here =30, x i = 40 = mean(x) = ( x i ) Variance= (x i x) = =45.8 (x i x) = 1374 = 14 S.D= 45.8 = 6.77 tutorial
3 3. The following table gives daily wages of workers in a factory. Calculate the standard deviation and coefficient of variation of the wages of the workers. wages o of workers d i = ( x i A ) c d i d i d i (A) d i = 31 d i = 39 Here =7, A=300, C=50, mean(x) = A + ( d i ) C = ( 31 7 ) 50 Variance= C [( d i ) ( d i ) ] S.D= 50 7 [7(39) ( 31) ] ( d i ) = 31, = = 88.5 d i = 39 = coefficient of variation = S.D 100 = x 3 tutorial
4 4. The scores of two cricketers A and B in 10 innings are given below, find who is better run getter and who is a more consistent player. Scores of A: x i Scores of B: y i (x i x) (x i x) (y i ) (y i y) (y i y) x i =540 (x i x) = y i =380 (y i y) = For cricketer A: x = x i =540 = 54; S. D = 10 (x i x) = = = For cricketer B: y = y i =380 = 38; S. D = 10 (y i y) = = 1068 = C.V of A = σ x = 100 = 60.8 and C.V of B = σ y x 54 y Since x > y, crickete A is a better run getter And C.V of A >C.V of B, A is also more consistent player = 100 = tutorial
5 5. Find the mean deviation from the mean of the following continuous frequency distribution d i = ( x i A ) c d i (A) =50 d i =10 = 47 Here =50, A=5, C=10, ( d i ) = 10, = 47 mean(x) = A + ( d i ) C x = 65 + ( ) 10 x = 65 3 x = 6 Mean D from mean = x i x = = tutorial
6 6. Find the mean deviation from the mean of the following continuous frequency distribution d i = ( x i A ) c d i (A) =100 d i =60 = 1040 Here =50, A=5, C=10, ( d i ) = 10, = 47 mean(x) = A + ( d i ) C x = 65 + ( ) 10 x = x = 71 Mean D from mean = x i x = = tutorial
7 7. Find the mean deviation from the median of the following continuous frequency distribution C.F x i M (A) , =1000 = 8175 Here =1000, =500, f=160, F=40 C=5, L=35 x i M = 8175 median(x) = L + ( P. C. F ). C f M = 35 + ( ) x = 35 + ( ) 5 Mean D from median = x i M = = x = = tutorial
8 8. Find the mean deviation from the median of the following continuous frequency distribution Arranging the observations in ascending order we get C.F x i M x i M (M) =30 = 149 Here =30, =15, Median=13 x i M = 149 Mean D from median = x i M = = tutorial
Roll No. : Invigilator's Signature : BIO-STATISTICS. Time Allotted : 3 Hours Full Marks : 70
Name : Roll No. : Invigilator's Signature :.. 2011 BIO-STATISTICS Time Allotted : 3 Hours Full Marks : 70 The figures in the margin indicate full marks. Candidates are required to give their answers in
More information2.1 Measures of Location (P.9-11)
MATH1015 Biostatistics Week.1 Measures of Location (P.9-11).1.1 Summation Notation Suppose that we observe n values from an experiment. This collection (or set) of n values is called a sample. Let x 1
More informationMeasures of Central Tendency
Statistics It is the science of assembling, analyzing, characterizing, and interpreting the collection of data. The general characterized of data: 1. Data shows a tendency to concentrate at certain values:
More informationProbability Solved Sums
Probability Solved Sums The mean is the usual Average, so add and then divide. The median is the middle value, so first rewrite the given number in ascending order. The mode is the number that is repeated
More informationQuantitative Tools for Research
Quantitative Tools for Research KASHIF QADRI Descriptive Analysis Lecture Week 4 1 Overview Measurement of Central Tendency / Location Mean, Median & Mode Quantiles (Quartiles, Deciles, Percentiles) Measurement
More information1 Paid Copy Don t Share With Anyone
Probability Solved Sums The mean is the usual Average, so add and then divide. The median is the middle value, so first rewrite the given number in ascending order. The mode is the number that is repeated
More informationBBA - I YEAR DJB1C : BUSINESS MATHEMATICS AND STATISTICS SYLLABUS
BBA - I YEAR DJBC : BUSINESS MATHEMATICS AND STATISTICS SYLLABUS UNIT I: Measures of centraltendency Mean, Median, Mode, G.M. and H.M. Dispersion Range Q.D. M.D. S.D. C.V. UNIT II: Simple Correlation and
More informationadditionalmathematicsstatisticsadditi onalmathematicsstatisticsadditionalm athematicsstatisticsadditionalmathem aticsstatisticsadditionalmathematicsst
additionalmathematicsstatisticsadditi onalmathematicsstatisticsadditionalm athematicsstatisticsadditionalmathem aticsstatisticsadditionalmathematicsst STATISTICS atisticsadditionalmathematicsstatistic
More informationOverview of Dispersion. Standard. Deviation
15.30 STATISTICS UNIT II: DISPERSION After reading this chapter, students will be able to understand: LEARNING OBJECTIVES To understand different measures of Dispersion i.e Range, Quartile Deviation, Mean
More information1 Measures of the Center of a Distribution
1 Measures of the Center of a Distribution Qualitative descriptions of the shape of a distribution are important and useful. But we will often desire the precision of numerical summaries as well. Two aspects
More informationWELCOME!! LABORATORY MATH PERCENT CONCENTRATION. Things to do ASAP: Concepts to deal with:
WELCOME!! Things to do ASAP: Read the course syllabus; information regarding testing, homework, lecture schedules, expectations and course objectives are all there Read the weekly overview; lecture objectives
More informationUNIT - 3 : STATISTICAL TOOLS AND INTERPRETATION Ch-6 MEASURES OF DISPERSION Points to rememeber * Dispersion is a measure of the variation of the items from central value. * The measures of dispersion
More information12.2. Measures of Central Tendency: The Mean, Median, and Mode
12.2. Measures of Central Tendency: The Mean, Median, and Mode 1 Objective A. Find the mean, median, and mode for a set of data. 2 Introduction Tongue Twister Averages Is there a relationship between the
More informationTEST 1 M3070 Fall 2003
TEST 1 M3070 Fall 2003 Show all work. Name: Problem 1. (10 points Below are the daily high temperatures, in degrees Fahrenheit, for Salt Lake City during July 2003 (31 days. The decimal point is 1 digit(s
More informationMALLOY PSYCH 3000 MEAN & VARIANCE PAGE 1 STATISTICS MEASURES OF CENTRAL TENDENCY. In an experiment, these are applied to the dependent variable (DV)
MALLOY PSYCH 3000 MEAN & VARIANCE PAGE 1 STATISTICS Descriptive statistics Inferential statistics MEASURES OF CENTRAL TENDENCY In an experiment, these are applied to the dependent variable (DV) E.g., MEASURES
More informationDetermining the Spread of a Distribution Variance & Standard Deviation
Determining the Spread of a Distribution Variance & Standard Deviation 1.3 Cathy Poliak, Ph.D. cathy@math.uh.edu Department of Mathematics University of Houston Lecture 3 Lecture 3 1 / 32 Outline 1 Describing
More informationNon-parametric tests, part A:
Two types of statistical test: Non-parametric tests, part A: Parametric tests: Based on assumption that the data have certain characteristics or "parameters": Results are only valid if (a) the data are
More informationChapter (3) Describing Data Numerical Measures Examples
Chapter (3) Describing Data Numerical Measures Examples Numeric Measurers Measures of Central Tendency Measures of Dispersion Arithmetic mean Mode Median Geometric Mean Range Variance &Standard deviation
More informationSlide 1. Slide 2. Slide 3. Pick a Brick. Daphne. 400 pts 200 pts 300 pts 500 pts 100 pts. 300 pts. 300 pts 400 pts 100 pts 400 pts.
Slide 1 Slide 2 Daphne Phillip Kathy Slide 3 Pick a Brick 100 pts 200 pts 500 pts 300 pts 400 pts 200 pts 300 pts 500 pts 100 pts 300 pts 400 pts 100 pts 400 pts 100 pts 200 pts 500 pts 100 pts 400 pts
More informationChapter 3. Data Description
Chapter 3. Data Description Graphical Methods Pie chart It is used to display the percentage of the total number of measurements falling into each of the categories of the variable by partition a circle.
More informationMgtOp 215 Chapter 3 Dr. Ahn
MgtOp 215 Chapter 3 Dr. Ahn Measures of central tendency (center, location): measures the middle point of a distribution or data; these include mean and median. Measures of dispersion (variability, spread):
More informationDifference in two or more average scores in different groups
ANOVAs Analysis of Variance (ANOVA) Difference in two or more average scores in different groups Each participant tested once Same outcome tested in each group Simplest is one-way ANOVA (one variable as
More informationHolidays Homework(10+1) Economics. 1 Calculate arithmetic mean with the help of following data.use direct method.
Holidays Homework(+1) Economics 1 Calculate arithmetic mean with the help of following data.use direct method. Wages : 0 0 Workers No. of : 1 Compute arithmetic mean by using short cut method. Salaries:
More informationQuartiles, Deciles, and Percentiles
Quartiles, Deciles, and Percentiles From the definition of median that it s the middle point in the axis frequency distribution curve, and it is divided the area under the curve for two areas have the
More informationHigher Secondary - First year STATISTICS Practical Book
Higher Secondary - First year STATISTICS Practical Book th_statistics_practicals.indd 07-09-08 8:00:9 Introduction Statistical tools are important for us in daily life. They are used in the analysis of
More informationWINTER 16 EXAMINATION
(ISO/IEC - 700-005 Certified) WINTER 6 EXAMINATION Model wer ject Code: Important Instructions to examiners: ) The answers should be examined by key words and not as word-to-word as given in the model
More informationZ score indicates how far a raw score deviates from the sample mean in SD units. score Mean % Lower Bound
1 EDUR 8131 Chat 3 Notes 2 Normal Distribution and Standard Scores Questions Standard Scores: Z score Z = (X M) / SD Z = deviation score divided by standard deviation Z score indicates how far a raw score
More informationMidterm 1 and 2 results
Midterm 1 and 2 results Midterm 1 Midterm 2 ------------------------------ Min. :40.00 Min. : 20.0 1st Qu.:60.00 1st Qu.:60.00 Median :75.00 Median :70.0 Mean :71.97 Mean :69.77 3rd Qu.:85.00 3rd Qu.:85.0
More informationMEASURES OF CENTRAL TENDENCY
MAT001-Statistics for Engineers MEASURES OF CENTRAL TENDENCY DESCRIPTIVE STATISTICAL MEASURES Graphical representation summarizes information in the data. In addition to the diagrammatic and graphic representations
More informationDescriptive Statistics Class Practice [133 marks]
Descriptive Statistics Class Practice [133 marks] The weekly wages (in dollars) of 80 employees are displayed in the cumulative frequency curve below. 1a. (i) (ii) Write down the median weekly wage. Find
More informationDescriptive Statistics
Sherif Khalifa Sherif Khalifa () Descriptive Statistics 1 / 34 Definition Measures of central tendency yield information about the center, or middle part, of a group of numbers. Mode Median Mean Percentiles
More informationGRAPHS AND STATISTICS Central Tendency and Dispersion Common Core Standards
B Graphs and Statistics, Lesson 2, Central Tendency and Dispersion (r. 2018) GRAPHS AND STATISTICS Central Tendency and Dispersion Common Core Standards Next Generation Standards S-ID.A.2 Use statistics
More informationMEASURES OF CENTRAL TENDENCY
INTRODUCTION: MEASURES OF CENTRAL TENDENCY Often, one encounters e term Measures of central tendency in a book on statistics (or an examination). One may also find mention of e term in a description of
More informationAuthor : Dr. Pushpinder Kaur. Educational Statistics: Mean Median and Mode
B.ED. PART- II ACADEMIC SESSION : 2017-2018 PAPER XVIII Assessment for Learning Lesson No. 8 Author : Dr. Pushpinder Kaur Educational Statistics: Mean Median and Mode MEAN : The mean is the average value
More informationUnit 2: Numerical Descriptive Measures
Unit 2: Numerical Descriptive Measures Summation Notation Measures of Central Tendency Measures of Dispersion Chebyshev's Rule Empirical Rule Measures of Relative Standing Box Plots z scores Jan 28 10:48
More informationChapter 3 Data Description
Chapter 3 Data Description Section 3.1: Measures of Central Tendency Section 3.2: Measures of Variation Section 3.3: Measures of Position Section 3.1: Measures of Central Tendency Definition of Average
More informationMODEL QUESTION FOR SA1 (FOR LATE BLOOMERS)
MODEL QUESTION FOR SA1 (FOR LATE BLOOMERS) SECTION A 1x4=4 1. Find the number of zeros in the following fig. 2. 3. If 4cotA = 3, find tan A. 4. If the less than type ogive and the more than type ogive
More informationStatistics I Chapter 2: Univariate data analysis
Statistics I Chapter 2: Univariate data analysis Chapter 2: Univariate data analysis Contents Graphical displays for categorical data (barchart, piechart) Graphical displays for numerical data data (histogram,
More informationWhere would you rather live? (And why?)
Where would you rather live? (And why?) CityA CityB Where would you rather live? (And why?) CityA CityB City A is San Diego, CA, and City B is Evansville, IN Measures of Dispersion Suppose you need a new
More informationMath 1 Summer Assignment 2017
Math 1 Summer Assignment 2017 Assignment Due: Monday, August 28, 2017 Name: The following packet contains topics and definitions that you will be required to know in order to succeed in Math 1 this year.
More information1. For which of these would you use a histogram to show the data? (a) The number of letters for different areas in a postman s bag.
Data Handling 1. For which of these would you use a histogram to show the data? (a) The number of letters for different areas in a postman s bag. (b) The height of competitors in an athletics meet. (c)
More informationDetermining the Spread of a Distribution
Determining the Spread of a Distribution 1.3-1.5 Cathy Poliak, Ph.D. cathy@math.uh.edu Department of Mathematics University of Houston Lecture 3-2311 Lecture 3-2311 1 / 58 Outline 1 Describing Quantitative
More informationStatistics I Chapter 2: Univariate data analysis
Statistics I Chapter 2: Univariate data analysis Chapter 2: Univariate data analysis Contents Graphical displays for categorical data (barchart, piechart) Graphical displays for numerical data data (histogram,
More informationDetermining the Spread of a Distribution
Determining the Spread of a Distribution 1.3-1.5 Cathy Poliak, Ph.D. cathy@math.uh.edu Department of Mathematics University of Houston Lecture 3-2311 Lecture 3-2311 1 / 58 Outline 1 Describing Quantitative
More informationStats Review Chapter 3. Mary Stangler Center for Academic Success Revised 8/16
Stats Review Chapter Revised 8/16 Note: This review is composed of questions similar to those found in the chapter review and/or chapter test. This review is meant to highlight basic concepts from the
More informationHypothesis Testing and Confidence Intervals (Part 2): Cohen s d, Logic of Testing, and Confidence Intervals
Hypothesis Testing and Confidence Intervals (Part 2): Cohen s d, Logic of Testing, and Confidence Intervals Lecture 9 Justin Kern April 9, 2018 Measuring Effect Size: Cohen s d Simply finding whether a
More informationGOYAL BROTHERS PRAKASHAN
Assignments in Mathematics Cass IX (Term 2) 14. STATISTICS IMPORTANT TERMS, DEFINITIONS AND RESULTS The facts or figures, which are numerica or otherwise, coected with a definite purpose are caed data.
More informationDesign of Experiments. Factorial experiments require a lot of resources
Design of Experiments Factorial experiments require a lot of resources Sometimes real-world practical considerations require us to design experiments in specialized ways. The design of an experiment is
More informationSTATISTICS. 1. Measures of Central Tendency
STATISTICS 1. Measures o Central Tendency Mode, median and mean For a sample o discrete data, the mode is the observation, x with the highest requency,. 1 N F For grouped data in a cumulative requency
More informationMath Maintenance Assignment
Math Maintenance Assignment Welcome to Honors Algebra 1! In order to ensure success in this course, there is a mandatory summer assignment packet. This packet is due on the first day of your math class
More informationStatistical Reports in the Magruder Program
Statistical Reports in the Magruder Program Statistical reports are available for each sample through LAB PORTAL with laboratory log in and on the Magruder web site. Review the instruction steps 11 through
More informationBasic Maths(M-I) I SCHEME. UNIT-I Algebra
Basic Maths(M-I) I SCHEME UNIT-I Algebra Prepared By : Sameer V. shaikh {Engr.sameer@gmail.com} {9765158158} Website : www.mechdiploma.com, www.diplomamaths.com, msbte.engg info.website Shaikh sir s Reliance
More information6. For any event E, which is associated to an experiment, we have 0 P( 7. If E 1
CHAPTER PROBABILITY Points to Remember :. An activity which gives a result is called an experiment.. An experiment which can be repeated a number of times under the same set of conditions, and the outcomes
More informationData Handling TEXTBOOK QUESTIONS SOLVED. Learn and Remember. Exercise 3.1 (Page No )
Data Handling Learn and Remember 1. The collection of facts which are expressed numerically is called data. 2. Arranging the data in the form of descending and ascending order is called array. 3. Frequency
More informationDescribing distributions with numbers
Describing distributions with numbers A large number or numerical methods are available for describing quantitative data sets. Most of these methods measure one of two data characteristics: The central
More informationKCP e-learning. test user - ability basic maths revision. During your training, we will need to cover some ground using statistics.
During your training, we will need to cover some ground using statistics. The very mention of this word can sometimes alarm delegates who may not have done any maths or statistics since leaving school.
More informationThe Normal Distribution. MDM4U Unit 6 Lesson 2
The Normal Distribution MDM4U Unit 6 Lesson 2 Normal Distributions Many data sets display similar characteristics The normal distribution is a way of describing a certain kind of "ideal" data set Although
More informationADMS2320.com. We Make Stats Easy. Chapter 4. ADMS2320.com Tutorials Past Tests. Tutorial Length 1 Hour 45 Minutes
We Make Stats Easy. Chapter 4 Tutorial Length 1 Hour 45 Minutes Tutorials Past Tests Chapter 4 Page 1 Chapter 4 Note The following topics will be covered in this chapter: Measures of central location Measures
More informationLecture # 31. Questions of Marks 3. Question: Solution:
Lecture # 31 Given XY = 400, X = 5, Y = 4, S = 4, S = 3, n = 15. Compute the coefficient of correlation between XX and YY. r =0.55 X Y Determine whether two variables XX and YY are correlated or uncorrelated
More informationRegression Analysis and Analysis of Variance
Prof. Dr. P. L. Davies Technische Universiteit Eindhoven 10. 05. 2006 Regression Analysis and Analysis of Variance Examination Question 1.1 (a) Let X 1,..., X n be i.i.d. random variables with the common
More informationAlgebra 1 Summer Assignment 2018
Algebra 1 Summer Assignment 2018 The following packet contains topics and definitions that you will be required to know in order to succeed in Algebra 1 this coming school year. You are advised to be familiar
More informationLecture 2. Descriptive Statistics: Measures of Center
Lecture 2. Descriptive Statistics: Measures of Center Descriptive Statistics summarize or describe the important characteristics of a known set of data Inferential Statistics use sample data to make inferences
More informationSolutionbank S1 Edexcel AS and A Level Modular Mathematics
file://c:\users\buba\kaz\ouba\s1_3_a_1.html Exercise A, Question 1 15 students do a mathematics test. Their marks are shown opposite. a Find the value of the median. b Find Q 1 and Q 3. 7 4 9 7 6 10 12
More informationClass 11 Maths Chapter 15. Statistics
1 P a g e Class 11 Maths Chapter 15. Statistics Statistics is the Science of collection, organization, presentation, analysis and interpretation of the numerical data. Useful Terms 1. Limit of the Class
More informationDr. Iyad Jafar. Adapted from the publisher slides
Computer Applications Lab Lab 9 Probability, Statistics, Interpolation, and Calculus Chapter 7 Dr. Iyad Jafar Adapted from the publisher slides Outline Statistics and Probability Histograms Normal and
More informationAddition of Center Points to a 2 k Designs Section 6-6 page 271
to a 2 k Designs Section 6-6 page 271 Based on the idea of replicating some of the runs in a factorial design 2 level designs assume linearity. If interaction terms are added to model some curvature results
More informationStatistics and parameters
Statistics and parameters Tables, histograms and other charts are used to summarize large amounts of data. Often, an even more extreme summary is desirable. Statistics and parameters are numbers that characterize
More informationTheoretical Foundations
Theoretical Foundations Sampling Distribution and Central Limit Theorem Monia Ranalli monia.ranalli@uniroma3.it Ranalli M. Theoretical Foundations - Sampling Distribution and Central Limit Theorem Lesson
More informationPROBABILITY DISTRIBUTION
PROBABILITY DISTRIBUTION DEFINITION: If S is a sample space with a probability measure and x is a real valued function defined over the elements of S, then x is called a random variable. Types of Random
More informationMEASURES OF DISPERSION
MEASURES OF DISPERSION Measure of Cetral Tedecy: Measures of Cetral Tedecy ad Dsperso ) Mathematcal Average: a) Arthmetc mea (A.M.) b) Geometrc mea (G.M.) c) Harmoc mea (H.M.) ) Averages of Posto: a) Meda
More informationT-Test QUESTION T-TEST GROUPS = sex(1 2) /MISSING = ANALYSIS /VARIABLES = quiz1 quiz2 quiz3 quiz4 quiz5 final total /CRITERIA = CI(.95).
QUESTION 11.1 GROUPS = sex(1 2) /MISSING = ANALYSIS /VARIABLES = quiz2 quiz3 quiz4 quiz5 final total /CRITERIA = CI(.95). Group Statistics quiz2 quiz3 quiz4 quiz5 final total sex N Mean Std. Deviation
More informationLecture 2 and Lecture 3
Lecture 2 and Lecture 3 1 Lecture 2 and Lecture 3 We can describe distributions using 3 characteristics: shape, center and spread. These characteristics have been discussed since the foundation of statistics.
More informationCIVL 7012/8012. Collection and Analysis of Information
CIVL 7012/8012 Collection and Analysis of Information Uncertainty in Engineering Statistics deals with the collection and analysis of data to solve real-world problems. Uncertainty is inherent in all real
More informationIntroduction to Statistics
Why Statistics? Introduction to Statistics To develop an appreciation for variability and how it effects products and processes. Study methods that can be used to help solve problems, build knowledge and
More informationMSc / PhD Course Advanced Biostatistics. dr. P. Nazarov
MSc / PhD Course Advanced Biostatistics dr. P. Nazarov petr.nazarov@crp-sante.lu 2-12-2012 1. Descriptive Statistics edu.sablab.net/abs2013 1 Outline Lecture 0. Introduction to R - continuation Data import
More informationDescribing Data: Numerical Measures
Describing Data: Numerical Measures Chapter 03 McGraw-Hill/Irwin Copyright 2013 by The McGraw-Hill Companies, Inc. All rights reserved. LEARNING OBJECTIVES LO 3-1 Explain the concept of central tendency.
More informationPractice problems from chapters 2 and 3
Practice problems from chapters and 3 Question-1. For each of the following variables, indicate whether it is quantitative or qualitative and specify which of the four levels of measurement (nominal, ordinal,
More informationStat 20: Intro to Probability and Statistics
Stat 20: Intro to Probability and Statistics Lecture 5: Summary Statistics Tessa L. Childers-Day UC Berkeley 30 June 2014 By the end of this lecture... You will be able to: Describe a data set by its:
More informationGrade 9 Data Handling - Probability, Statistics
ID : ae-9-data-handling-probability-statistics [1] Grade 9 Data Handling - Probability, Statistics For more such worksheets visit www.edugain.com Answer t he quest ions (1) The numbers 1 to 19 are written
More informationVariance Decomposition and Goodness of Fit
Variance Decomposition and Goodness of Fit 1. Example: Monthly Earnings and Years of Education In this tutorial, we will focus on an example that explores the relationship between total monthly earnings
More informationSection 3. Measures of Variation
Section 3 Measures of Variation Range Range = (maximum value) (minimum value) It is very sensitive to extreme values; therefore not as useful as other measures of variation. Sample Standard Deviation The
More informationAMS 5 NUMERICAL DESCRIPTIVE METHODS
AMS 5 NUMERICAL DESCRIPTIVE METHODS Introduction A histogram provides a graphical description of the distribution of a sample of data. If we want to summarize the properties of such a distribution we can
More informationPerhaps the most important measure of location is the mean (average). Sample mean: where n = sample size. Arrange the values from smallest to largest:
1 Chapter 3 - Descriptive stats: Numerical measures 3.1 Measures of Location Mean Perhaps the most important measure of location is the mean (average). Sample mean: where n = sample size Example: The number
More informationData Summarization. Andrew Jaffe Instructor
Module 7 Data Summarization Andrew Jaffe Instructor Data Summarization Basic statistical summarization mean(x): takes the mean of x sd(x): takes the standard deviation of x median(x): takes the median
More informationDescribing Data: Numerical Measures. Chapter 3
Describing Data: Numerical Measures Chapter 3 Learning Objectives Calculate the arithmetic mean, weighted mean median, and the mode. Explain the characteristics, uses, advantages, and disadvantages of
More informationUnivariate data. topic 12. Why learn this? What do you know? Learning sequence
topic 12 Univariate data 12.1 Overview Why learn this? According to the novelist Mark Twain, There are three kinds of lies: lies, damned lies and statistics. There is so much information in our lives,
More informationChapter. Numerically Summarizing Data. Copyright 2013, 2010 and 2007 Pearson Education, Inc.
Chapter 3 Numerically Summarizing Data Section 3.1 Measures of Central Tendency Objectives 1. Determine the arithmetic mean of a variable from raw data 2. Determine the median of a variable from raw data
More informationUNCORRECTED PAGE PROOFS
STATiSTicS And probabilitybiliity Topic 12 Univariate data 12.1 Overview Why learn this? According to the novelist Mark Twain, There are three kinds of lies: lies, damned lies and statistics. There is
More informationUnit 2. Describing Data: Numerical
Unit 2 Describing Data: Numerical Describing Data Numerically Describing Data Numerically Central Tendency Arithmetic Mean Median Mode Variation Range Interquartile Range Variance Standard Deviation Coefficient
More information4. On the number line below, what number does point M represent? 9. What is the coordinate of point A?
McCloskey Middle School - Grade 7 Summer Math Packet Name: Date:. A hardware store sells boxes of nails. The nails are 5, 9 6, 4, and inch in length. If the 2 boxes of nails are to be arranged by nail
More informationUnit Two Descriptive Biostatistics. Dr Mahmoud Alhussami
Unit Two Descriptive Biostatistics Dr Mahmoud Alhussami Descriptive Biostatistics The best way to work with data is to summarize and organize them. Numbers that have not been summarized and organized are
More informationHeteroscedasticity 1
Heteroscedasticity 1 Pierre Nguimkeu BUEC 333 Summer 2011 1 Based on P. Lavergne, Lectures notes Outline Pure Versus Impure Heteroscedasticity Consequences and Detection Remedies Pure Heteroscedasticity
More informationMIDTERM EXAMINATION (Spring 2011) STA301- Statistics and Probability
STA301- Statistics and Probability Solved MCQS From Midterm Papers March 19,2012 MC100401285 Moaaz.pk@gmail.com Mc100401285@gmail.com PSMD01 MIDTERM EXAMINATION (Spring 2011) STA301- Statistics and Probability
More informationThe Union and Intersection for Different Configurations of Two Events Mutually Exclusive vs Independency of Events
Section 1: Introductory Probability Basic Probability Facts Probabilities of Simple Events Overview of Set Language Venn Diagrams Probabilities of Compound Events Choices of Events The Addition Rule Combinations
More informationMathematics. Mock Paper. With. Blue Print of Original Paper. on Latest Pattern. Solution Visits:
10 th CBSE{SA I} Mathematics Mock Paper With Blue Print of Original Paper on Latest Pattern Solution Visits: www.pioneermathematics.com/latest_updates www.pioneermathematics.com S.C.O. - 36, Sector 40
More informationMeasures of Central Tendency
Measures of Central Tendency Summary Measures Summary Measures Central Tendency Mean Median Mode Quartile Range Variance Variation Coefficient of Variation Standard Deviation Measures of Central Tendency
More informationCHAPTER 14 STATISTICS Introduction
238 MATHEMATICS STATISTICS CHAPTER 14 14.1 Introduction Everyday we come across a wide variety of informations in the form of facts, numerical figures, tables, graphs, etc. These are provided by newspapers,
More informationQuestion Bank In Mathematics Class IX (Term II)
Question Bank In Mathematics Class IX (Term II) PROBABILITY A. SUMMATIVE ASSESSMENT. PROBABILITY AN EXPERIMENTAL APPROACH. The science which measures the degree of uncertainty is called probability.. In
More informationF78SC2 Notes 2 RJRC. If the interest rate is 5%, we substitute x = 0.05 in the formula. This gives
F78SC2 Notes 2 RJRC Algebra It is useful to use letters to represent numbers. We can use the rules of arithmetic to manipulate the formula and just substitute in the numbers at the end. Example: 100 invested
More informationIn order to carry out a study on employees wages, a company collects information from its 500 employees 1 as follows:
INTRODUCTORY ECONOMETRICS Dpt of Econometrics & Statistics (EA3) University of the Basque Country UPV/EHU OCW Self Evaluation answers Time: 21/2 hours SURNAME: NAME: ID#: Specific competences to be evaluated
More information