Please write your name and UNI-ID on the attendance sheet

Slides:



Advertisements
Similar presentations
Data Handling II: Describing and Depicting your Data Dr Yanzhong Wang Lecturer in Medical Statistics Division of Health and Social Care Research King's.
Advertisements

Unit 16: Statistics Sections 16AB Central Tendency/Measures of Spread.
LECTURE 7 THURSDAY, 11 FEBRUARY STA291 Fall 2008.
Statistics.
Basic Business Statistics (10th Edition)
1 Business 90: Business Statistics Professor David Mease Sec 03, T R 7:30-8:45AM BBC 204 Lecture 11 = Finish Chapter Numerical Descriptive Measures (NDM)
© 2002 Prentice-Hall, Inc.Chap 3-1 Basic Business Statistics (8 th Edition) Chapter 3 Numerical Descriptive Measures.
Descriptive Statistics A.A. Elimam College of Business San Francisco State University.
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.
Descriptive Statistics Statistical Notation Measures of Central Tendency Measures of Variability Estimating Population Values.
1 Economics 240A Power One. 2 Outline w Course Organization w Course Overview w Resources for Studying.
Chapter 13 Analyzing Quantitative data. LEVELS OF MEASUREMENT Nominal Measurement Ordinal Measurement Interval Measurement Ratio Measurement.
Chapter 14 Analyzing Quantitative Data. LEVELS OF MEASUREMENT Nominal Measurement Nominal Measurement Ordinal Measurement Ordinal Measurement Interval.
QM Spring 2002 Statistics for Decision Making Descriptive Statistics.
1 Economics 240A Power One. 2 Outline w Course Organization w Course Overview w Resources for Studying.
1 Basic statistics Week 10 Lecture 1. Thursday, May 20, 2004 ISYS3015 Analytic methods for IS professionals School of IT, University of Sydney 2 Meanings.
Official release of STATISTICAL TOOLS An Overview of Common Applications in Social Sciences Manfred te Grotenhuis Theo van der Weegen.
© 2003 Prentice-Hall, Inc.Chap 3-1 Business Statistics: A First Course (3 rd Edition) Chapter 3 Numerical Descriptive Measures.
Business Statistics BU305 Chapter 3 Descriptive Stats: Numerical Methods.
PPA 501 – A NALYTICAL M ETHODS IN A DMINISTRATION Lecture 3b – Fundamentals of Quantitative Research.
Descriptive Statistics Roger L. Brown, Ph.D. Medical Research Consulting Middleton, WI Online Course #1.
Practice 1 Tao Yuchun Medical Statistics
Descriptive Statistics
Descriptive Statistics1 LSSG Green Belt Training Descriptive Statistics.
McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 3 Descriptive Statistics: Numerical Methods.
Describing Data Using Numerical Measures. Topics.
Determination of Sample Size: A Review of Statistical Theory
L. Liu PM Outreach, USyd.1 Survey Analysis. L. Liu PM Outreach, USyd.2 Types of research Descriptive Exploratory Evaluative.
Measures of Central Tendency: The Mean, Median, and Mode
Introduction to Statistics Santosh Kumar Director (iCISA)
Summary Statistics and Mean Absolute Deviation MM1D3a. Compare summary statistics (mean, median, quartiles, and interquartile range) from one sample data.
Lecturer’s desk Physics- atmospheric Sciences (PAS) - Room 201 s c r e e n Row A Row B Row C Row D Row E Row F Row G Row H Row A
Describing Data Descriptive Statistics: Central Tendency and Variation.
Statistical Analysis of Data. What is a Statistic???? Population Sample Parameter: value that describes a population Statistic: a value that describes.
MODULE 3: DESCRIPTIVE STATISTICS 2/6/2016BUS216: Probability & Statistics for Economics & Business 1.
1 Day 1 Quantitative Methods for Investment Management by Binam Ghimire.
Why do we analyze data?  It is important to analyze data because you need to determine the extent to which the hypothesized relationship does or does.
Why do we analyze data?  To determine the extent to which the hypothesized relationship does or does not exist.  You need to find both the central tendency.
Statistics My name: Huiyuan Liu---刘慧媛 My My address: Room 307 No.1 Teaching Building.
Statistics -Descriptive statistics 2013/09/30. Descriptive statistics Numerical measures of location, dispersion, shape, and association are also used.
Statistics and probability Dr. Khaled Ismael Almghari Phone No:
© 1999 Prentice-Hall, Inc. Chap Measures of Central Location Mean, Median, Mode Measures of Variation Range, Variance and Standard Deviation Measures.
Descriptive Statistics ( )
Statistical Methods Michael J. Watts
Statistics in Management
Populations.
Statistical Methods Michael J. Watts
Summary of Prev. Lecture
Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10: :50 Mondays, Wednesdays.
Module 6: Descriptive Statistics
26134 Business Statistics Week 3 Tutorial
BUS 308Competitive Success/tutorialrank.com
BUS 308 MENTOR Lessons in Excellence--bus308mentor.com.
BUS 308 HELPS Perfect Education/ bus308helps.com.
BUS 308 Education for Service-- tutorialrank.com.
BUS 308 HELPS Education for Service-- bus308helps.com.
Theme 4 Describing Variables Numerically
IB Psychology Today’s Agenda: Turn in:
IB Psychology Today’s Agenda: Turn in: Work Day… Take out:
STA 291 Spring 2008 Lecture 5 Dustin Lueker.
STA 291 Spring 2008 Lecture 5 Dustin Lueker.
Descriptive Statistics
Univariate Statistics
Mean, Median, Mode The Mean is the simple average of the data values. Most appropriate for symmetric data. The Median is the middle value. It’s best.
6A Types of Data, 6E Measuring the Centre of Data
Descriptive Statistics
Business and Economics 7th Edition
Numerical Descriptive Measures
Descriptive statistics for groups:
Introductory Statistics
Presentation transcript:

Please write your name and UNI-ID on the attendance sheet Please make sure you are attending the tutorial you enrolled in Please log on to wattle and read through the tutorial questions

Research School of Finance, Actuarial Studies and Applied Statistics STAT7055 Tutorial Week 2 NingNing Wang (Tony) Research School of Finance, Actuarial Studies and Applied Statistics Updated 28th Feb 2017

Introduction Miscellaneous about the course Tutorial 1

Introduction NingNing Wang (Tony) Bachelor and Master of Actuarial Studies in ANU u4975898@anu.edu.au www.linkedin.com/in/ningningwang/ Consultation time Wed 1pm~4pm CBE 3.09 (Statistics Consultation Room)

Your assessments: Quiz 5% (or 0%) Mid 30% (or 35%) Final 65%

Communication – in English Send any questions or any concerns to my email address using your ANU email Attend the consultations if you have any questions Do your homework Finish the tutorial questions At least read through them

Topic 1 - Descriptive Statistics Tutorial Week 2 Topic 1 - Descriptive Statistics

Summary Population vs sample Parameters (μ, σ) vs statistics 𝑋 , s Categorical vs Numerical Nominal vs Ordinal Discrete vs Continuous

Central Tendency: mean (arithmetic), median, mode Quantile & Percentile Range & IQR Variance and Covariance Correlation Coefficient

Question 1 Variable Features Estimated Price Number of Bedrooms Size Pool Present Distance from Civic Insulation rating Suburb Number of bathrooms Type of Internet

Question 1 Variable Features Estimated Price Continuous Number of Bedrooms Discrete (Count) Size Pool Present Nominal (Yes/No) Distance from Civic Insulation rating Ordinal (categories) Suburb Nominal Number of bathrooms Discrete Type of Internet

Question 2 Let X be the marketing expenditure Y be the number of sales Z be the number of rainy days

Question 2 Month Xi Yi ( 𝑿 𝒊 − 𝑿 )( 𝒀 𝒊 − 𝒀 ) 1 4150 778 1944971.88 2 ( 𝑿 𝒊 − 𝑿 )( 𝒀 𝒊 − 𝒀 ) 1 4150 778 1944971.88 2 3000 779 3103828.13 3 2500 4200 -8621559.38 4 10600 250 -6961146.88 5 12000 300 -8818621.88 6 8000 6000 8107378.13 7 1500 1319315.63 8 6850 500 -998490.63 Mean = 6075 Mean = 1788.375 ∑=-10924325.00

Question 2 𝑠 𝑋 =𝑐 𝑣 𝑋 ∗ 𝑋 =3905.3077, 𝑠 𝑌 =𝑐 𝑣 𝑌 ∗ 𝑌 = 2135.3603 𝑠 𝑋 =𝑐 𝑣 𝑋 ∗ 𝑋 =3905.3077, 𝑠 𝑌 =𝑐 𝑣 𝑌 ∗ 𝑌 = 2135.3603 𝑠 𝑋𝑌 = −10924325 8−1 =−1560617.86 𝑟 𝑋𝑌 = −1560617.86 3905.3077∗2135.3603 =−0.1871 𝑍 =12.125, 𝑠 𝑧 =𝑐 𝑣 𝑧 ∗ 𝑍 =7.9541 𝑟 𝑍𝑌 = 14012.23 7.9541∗2135.3603 =0.8250

Question 5 Data n=11 13 26 22 16 18 28 14 15 15 17 25 𝜇=19, 𝜎 2 = 1 𝑁 𝑖=1 𝑁 𝑋 𝑖 −𝜇 2 = 282 11 =25.6364

Question 5 Sample 𝑿 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 13,22,18,16 17.25 1233 26,15,17,15 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 13,22,18,16 17.25 1233 26,15,17,15 18.25 1415 14,18,15,25 18 1370 25,14,16,17 1366 13,26,25,18 20.5 1794

Question 5 Sample 𝑿 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 − 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 𝒏 𝒔 𝟐 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 − 𝒊=𝟏 𝒏 𝑿 𝒊 𝟐 𝒏 𝒔 𝟐 (using n-1) 𝒔 ∗𝟐 (using n) 13,22,18,16 17.25 1233 42.75 14.25 10.6875 26,15,17,15 18.25 1415 82.75 27.5833 20.6875 14,18,15,25 18 1370 74 24.6667 18.5 25,14,16,17 1366 70 23.3333 17.5 13,26,25,18 20.5 1794 113 37.6667 28.25 average 25.5 19.125

Question 3 Mean = 18.55 9 11 12 12 12 13 14 20 20 35 46 Median = 13, Mode = 12 𝐿 𝑝 = 𝑛+1 𝑝 100 L25 = 3, L75 = 9, L10 = 1.2, L60 = 7.2 9+0.2*(11-9)=9.4, 14+0.2*(20-14)=15.2 L=7.25, 60.4167