STAT 110 INTRODUCTION TO DESCRIPTIVE STATISTICS Fall‚ 2006 Lecture Notes Joshua M. Tebbs Department of Statistics The University of South Carolina TABLE OF CONTENTS STAT 110‚ J. TEBBS Contents 1 Where Do Data Come From? 1 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Individuals‚ variables‚ and data . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Observational studies . . . . . . . . . . . . . . . .
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Step 1- Identify the problem Develop a problem statement- What are you going to investigate (use the 6 characteristics of a good problem statement) 1. Be interested in the problem 2. Have a manageable scope 3. Be comfortable in terms of the knowledge‚ time‚ and resources needed to investigate the problem 4. Be able to collect and analyze numerical data 5. Must be a practical or theoretical reason for you to research the problem 6. It must be ethical for you to investigate the problem
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Statistics – Lab #6 Statistical Concepts: * Data Simulation * Discrete Probability Distribution * Confidence Intervals Calculations for a set of variables Mean Median 3.2 3.5 4.5 5.0 3.7 4.0 3.7 3.0 3.1 3.5 3.6 3.5 3.1 3.0 3.6 3.0 3.8 4.0 2.6 2.0 4.3 4.0 3.5 3.5 3.3 3.5 4.1 4.5 4.2 5.0 2.9 2.5 3.5 4.0 3.7 3.5 3.5 3.0 3.3 4.0 Calculating Descriptive Statistics Descriptive Statistics: Mean‚ Median Variable N N* Mean SE Mean StDev Minimum
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B6014 MANAGERIAL STATISTICS Course Description: This course introduces students to basic concepts in probability and statistics of relevance to managerial decision making. Topics include basic data analysis‚ random variables and probability distributions‚ sampling distributions‚ interval estimation‚ hypothesis testing and regression. Numerous examples are chosen from quality-control applications‚ finance‚ marketing and management. Type and Length of Exam: Open book‚ 3 hours‚ calculator such as HP-12C
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Satoru SHIMOKAWA‚ SOSC1100‚ Fall 2013 SOSC1100 Elementary Statistics for Social Research [Common Core (QR) for 4 year program] Fall 2013 Lectures: Wed and Fri‚ 13:30-14:50 / Rm. 4620‚ Academic Building (Lift 31-32) Course Website: http://lmes2.ust.hk INSTRUCTOR: SHIMOKAWA‚ Satoru OFFICE: 3370 Academic Building EMAIL: sosatoru@ust.hk OFFICE HOURS: Fridays‚ 3:00pm – 5:00pm TEACHING ASSISTANT: Stephen Choy OFFICE: 3001 EMAIL: choyho@ust.hk OFFICE HOURS: TBA 1. Course Description: This
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PROJECT C MATH 533 INSTRUCTOR Prof AMIR SADRAIN 1. Generate a scatterplot for CREDIT BALANCE vs SIZE Regression Analysis: Credit Balance ($) versus Size 2. Determine the equation of the "best fit" line‚ which describes the relationship between CREDIT BALANCE and SIZE. There is a slight positive relationship between credit balance and size The regression equation is Credit Balance ($) = 2591 + 403 Size 3. Determine the
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Case Study 3 According to the capital Asset pricing model (CAPM)‚ the risk associated with a capital asset is proportional to the slope obtaining by regressing the asset’s past returns with the corresponding returns of the average portfolio called the market portfolio. (The return of the market portfolio represents the return earned by the average investor. It is a weighted average of the returns from all the assets in the market). The larger the slope of an asset‚ the larger is the risk associated
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Running head: [M1A BUS210] [M1A BUS210] Anthony Johnson Allied American University Author Note This paper was prepared for [Business Statistics I]‚ [M1A] taught by [John Hannon]. PART I: APPLICATION Directions: Please answer each of the following questions (responses should be at least two paragraphs in length and be written in complete sentences‚ if applicable). Show essential calculations‚ if applicable. 1. Describe the difference between a population and a sample. A population
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chapter 1: STATS – STATISTICS DATA AND STATISTICAL THINKING 1.1 The science of statistics * Statistics - is the science of data. It involves collecting‚ classifying‚ summarising‚ organising‚ analysing‚ and interpreting numerical information. 1.2 types of statistical applications in business * Descriptive Statistics - describe collected data. Utilizes numerical and graphical methods to look for patterns in data‚ summarize the information in the data and to present the information in a
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(-3.5)/1.6396 = -2.1347 Critical Value: Zα/2= Z0.05/2= @qnorm(1-0.05/2)= 1.96 When comparing the test statistic to the critical value: Z=2.1347>1.96‚ we reject the null hypothesis. We can calculate the P-value using the EViews command: Show @tdist (t‚ d.f) In this EViews command‚ t stands for the appropriate test statistic and d.f are the degrees of freedom. The appropriate test statistic was calculated above‚ namely Z=2.1347. For the degrees of freedom‚ we can insert NA+NB-2. Show @tdist (2
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