Lab 2. Analysis of Observational Study/Calculations with SPSS
|
|
- Vincent Wilkinson
- 5 years ago
- Views:
Transcription
1 Lab 2 Analysis of Observational Study/Calculations with SPSS
2 What does an article look like? Title/Title Page Abstract Introduction Method Results Discussion References
3 What does an article look like? Resources See Appendix A in your book for guidance and examples. WARNING some things have APA rules have changed since the book s publication. Purdue Online Writing Lab (OWL) is a good resource for APA styling
4 RUNNING HEAD: Short Title 1 Title Name(s) Affiliation Author Note Short Title 2 Abstract Short Title 3 Title Short Title 4 Method Subjects Apparatus Procedure Short Title 5 Results Short Title 6 Discussion Short Title 8 References Short Title 9 Footnotes Short Title 10 Table 1 Title of Table Short Title 11 (put figures here with one figure per page) Figure
5 General Formating Tidbits Margins are 1 inch left, right, top, bottom Font is 12 point Times New Roman Double Space EVERYTHING Round numbers to two decimal places Page numbers go at the top right except on Figure pages
6 Results Direct the reader to data that seem most relevant to the purpose of the research. Structure 1. State the purpose of the analysis. 2. Identify the descriptive statistic to be used to summarize the results. May report interrater reliability here. 3. Present a summary of this descriptive statistic across conditions in the text itself, in a table, or in a figure. If you use a table or figure point out the major finding the reader should focus on. 4. Present the inferential statistics that are relevant for evaluating the descriptive statistics. 5. State the conclusion that follows from each test, but do not discuss implications. No causal statements!
7 Schachter et al. (1991) Do the departments differ from each other? Do the disciplines differ from each other? The results of these observations are in Table 1, which presents the mean uhs per minute of speaking for these 10 departments. Ignoring momentarily the a priori assignment of departments to the humanities or sciences, let us ask first if these 10 departments differ from one another in their lecturers' tendency to use uhs and ahs. They do, F(9,35) = 2.87, p <.01. It is also evident that, with the exception of philosophy, these differences correspond to the sciencesversus-humanities distinction, for the natural sciences average 1.39 uhs per minute in their lectures; the social sciences, 3.84; and the humanities, 4.85, F(2,42) = 6.46, p <.01. The natural sciences differ, using protected t tests, from the social sciences ( p <.02) and from the humanities (p <.01), whereas the social sciences and the humanities do not differ significantly from one another.
8 What if there were just 2 lectures? Imagine if Schachter et al. (1991) had only compared 2 lectures (Biology vs Art History). Then their write up might have looked a lot different. As a test whether lecturers in the natural sciences use more filled pauses than lecturers in the arts and humanities, the number of uhs lecturers from each discipline used per minute were recorded. Inconspicuous observers recorded the data during the lectures over the course of the semester. Interrater reliability for the number of uhs recorded per mintue was performed between a subset of observers to determine consistency among raters. The interrater reliability was found to have an 92% overlap. Biology lecturers used on average 1.13 uhs per minute (SD = 1). Art and history lecturers, representing the arts and humanities expressed 6.06 uhs per minute (SD = 2). The difference between the two disciplines was significant, t(8) = 4.4, p <.01. Art and history lecturers appear to use more uhs per minute compared to biology lecturers.
9 What if there were just 2 lectures? 1) State the purpose of the analysis. As a test whether lecturers in the natural sciences use more filled pauses than lecturers in the arts and humanities, the number of uhs lecturers from each discipline used per minute were recorded. Inconspicuous observers recorded the data during the lectures over the course of the semester. Interrater reliability for the number of uhs recorded per mintue was performed between a subset of observers to determine consistency among raters. The interrater reliability was found to have an 92% overlap. A subset of Biology lecturers used on average 1.13 uhs per minute (SD = 1). Art and history lecturers, representing the arts and humanities expressed 6.06 uhs per minute (SD = 2). The difference between the two disciplines was significant, t(8) = 4.4, p <.01. Art and history lecturers appear to use more uhs per minute compared to biology lecturers.
10 What if there were just 2 lectures? 1) State the purpose of the analysis. 2) Identify the descriptive statistic to be used to summarize the results. May report interrater reliability here. As a test whether lecturers in the natural sciences use more filled pauses than lecturers in the arts and humanities, the number of uhs lecturers from each discipline used per minute were recorded. Inconspicuous observers recorded the data during the lectures over the course of the semester. Interrater reliability for the number of uhs recorded per mintue was performed between a subset of observers to determine consistency among raters. The interrater reliability was found to have an 92% overlap. Biology lecturers used on average 1.13 uhs per minute (SD = 1). Art and history lecturers, representing the arts and humanities expressed 6.06 uhs per minute (SD = 2). The difference between the two disciplines was significant, t(8) = 4.4, p <.01. Art and history lecturers appear to use more uhs per minute compared to biology lecturers.
11 What if there were just 2 lectures? 1) State the purpose of the analysis. 2) Identify the descriptive statistic to be used to summarize the results. May report interrater reliability here. 3) Present a summary of this descriptive statistic across conditions in the text itself, in a table, or in a figure. As a test whether lecturers in the natural sciences use more filled pauses than lecturers in the arts and humanities, the number of uhs lecturers from each discipline used per minute were recorded. Inconspicuous observers recorded the data during the lectures over the course of the semester. Interrater reliability for the number of uhs recorded per mintue was performed between a subset of observers to determine consistency among raters. The interrater reliability was found to have an 92% overlap. Biology lecturers used on average 1.13 uhs per minute (SD = 1). Art and history lecturers, representing the arts and humanities expressed 6.06 uhs per minute (SD = 2). The difference between the two disciplines was significant, t(8) = 4.4, p <.01. Art and history lecturers appear to use more uhs per minute compared to biology lecturers.
12 What if there were just 2 lectures? 1) State the purpose of the analysis. 2) Identify the descriptive statistic to be used to summarize the results. May report interrater reliability here. 3) Present a summary of this descriptive statistic across conditions in the text itself, in a table, or in a figure. 4) Present the inferential statistics that are relevant for evaluating the descriptive statistics. As a test whether lecturers in the natural sciences use more filled pauses than lecturers in the arts and humanities, the number of uhs lecturers from each discipline used per minute were recorded. Inconspicuous observers recorded the data during the lectures over the course of the semester. Interrater reliability for the number of uhs recorded per mintue was performed between a subset of observers to determine consistency among raters. The interrater reliability was found to have an 92% overlap. Biology lecturers used on average 1.13 uhs per minute (SD = 1). Art and history lecturers, representing the arts and humanities expressed 6.06 uhs per minute (SD = 2). The difference between the two disciplines was significant, t(8) = 4.4, p <.01. Art and history lecturers appear to use more uhs per minute compared to biology lecturers.
13 What if there were just 2 lectures? 1) State the purpose of the analysis. 2) Identify the descriptive statistic to be used to summarize the results. May report interrater reliability here. 3) Present a summary of this descriptive statistic across conditions in the text itself, in a table, or in a figure. 4) Present the inferential statistics that are relevant for evaluating the descriptive statistics. 5) State the conclusion that follows from each test, but do not discuss implications. No causal statements! As a test whether lecturers in the natural sciences use more filled pauses than lecturers in the arts and humanities, the number of uhs lecturers from each discipline used per minute were recorded. Inconspicuous observers recorded the data during the lectures over the course of the semester. Interrater reliability for the number of uhs recorded per mintue was performed between a subset of observers to determine consistency among raters. The interrater reliability was found to have an 92% overlap. Biology lecturers used on average 1.13 uhs per minute (SD = 1). Art and history lecturers, representing the arts and humanities expressed 6.06 uhs per minute (SD = 2). The difference between the two disciplines was significant, t(8) = 4.4, p <.01. Art and history lecturers appear to use more uhs per minute compared to biology lecturers.
14 What if there were just 2 lectures? 1) State the purpose of the analysis. 2) Identify the descriptive statistic to be used to summarize the results. May report interrater reliability here. 3) Present a summary of this descriptive statistic across conditions in the text itself, in a table, or in a figure. 4) Present the inferential statistics that are relevant for evaluating the descriptive statistics. 5) State the conclusion that follows from each test, but do not discuss implications. No causal statements! As a test whether lecturers in the natural sciences use more filled pauses than lecturers in the arts and humanities, the number of uhs lecturers from each discipline used per minute were recorded. Inconspicuous observers recorded the data during the lectures over the course of the semester. Interrater reliability for the number of uhs recorded per mintue was performed between a subset of observers to determine consistency among raters. The interrater reliability was found to have an 92% overlap. Biology lecturers used on average 1.13 uhs per minute (SD = 1). Art and history lecturers, representing the arts and humanities expressed 6.06 uhs per minute (SD = 2). The difference between the two disciplines was significant, t(8) = 4.4, p <.01. Art and history lecturers appear to use more uhs per minute compared to biology lecturers.
15
16 What kind of data do you have? For now focus on your dependent variable. Do you have numerical, continuous data? Example: amount of coffee consumed in ounces, height of students, etc. Or do you have discrete, categorical data? Example: Type of coffee drinks, gender, favorite colors.
17 If you have continuous data... We generally summarize the data with means and standard deviations. As long as we can reasonably assume that One observation is independent from another observation. You can reasonably assume the sampling distribution of the mean is normal.
18 How to generate descriptive statistics once data is entered into SPSS. Analysis Descriptive Statistics Explore
19 The Explore Window When you choose Analyze >> Descriptives >> Explore this window will appear. Drop the variable you want descriptives on into the Dependent List (e.g., DrinkSize, which is the Dependent Variable (DV)). If you have an Independent Variable (IV) that has a small number of levels (e.g., TimeOfDay) then drop that variable into the Factor List. Click OK. SPSS will calculate descriptive statistics conditional on each level of the IV factor.
20 An output window will appear Morning M = 8.40 SD = 3.28 Afternoon M = SD = 5.02
21 If you want to run a t-test... Analyze Compare Means Independent-Samples T Test
22 Independent Sample t-test Window Drop your DV (e.g., DrinkSize) into Test Variables Drop you IV (e.g., TimeOfDay) in Grouping Variables Don t forget to Define Groups...
23 Define Groups With the grouping variable highlighted, press Define Groups Once you are in Define Groups (directly below)you must tell SPSS what the values of the grouping variable (IV) are. Enter the values for the IV After you have it set up -Click Continue -Click OK
24 The output looks like this The important parts!
25 Basic Reporting of Results When you describe your data with means and standard deviations and make inferences with t-tests use a sentence like this to describe your data: Larger drinks were observed in the afternoon hours (M = 16.80, SD = 5.02) than in the morning hours (M = 8.40, SD = 3.28; t(8) = -3.13, p <.05). Notice M, SD, t, and p are all italicized.
26 If you have categorical data... We summarize the data in proportions or sometimes frequencies. Again we assume independence between observations. Also generally require large sample sizes, at least 5 observations per cell or condition.
27 Chi-Square Test Attitude Against For Total Democrat Party Republican Total Can we conclude that people in different parties have different attitudes? Conceptually we are interested whether knowing something about the political party tells us something about people s attitudes. The Chi-Square test examines if there is a relationship between political party and the attitude one has.
28 How to generate descriptive statistics once data are entered in SPSS. If you hit this 1<-> A button you can go back and fourth between the assigned numbers and the Value Names you can assign by clicking on the Variable View at the bottom of the SPSS window. This is also where you name your columns at.
29 How to generate descriptive statistics once data are entered in SPSS. Analyze Descriptive Statistics Crosstabs
30 The Crosstabs Window When you choose Analyze >> Descriptive Statistics >> Crosstabs this window will appear. Drop the variable you want into rows (e.g., PolAffiliation). I typically put the IV here. Drop the other variable (e.g., Attitude, or DV) into columns. After you do that press Statistics
31 Choose Statistics Select Chi-Square After you have it set up -Click Continue -Click OK
32 An output window will appear This table will tell you about the distribution of observations. For example, 8 Democrats out of 10 were against. This table will tell you about the outcome of the Pearson Chi-Square test of independence. Use the top line Pearson Chi-Square
33 Writing up the results When you describe your data with proportions and make inferences with Chi-Square tests, we use a sentence like this to describe the data: Seventy percent of republicans reported strong attitudes for the bill as compared to only 20% of Democrats, χ 2 (1, N = 20) = 5.1, p <.05. Note in APA style when you start a sentence with a number you spell it out. Degrees of freedom
34 Now, crunch that data!
CHAPTER FIVE CROSSTABS PROCEDURE
CHAPTER FIVE CROSSTABS PROCEDURE 5.0 Introduction This chapter focuses on how to compare groups when the outcome is categorical (nominal or ordinal) by using SPSS. The aim of the series of exercise is
More informationWhat is statistics? Prof. Jacob M. Montgomery. Quantitative Political Methodology (L32 363) August 31, 2016
What is statistics? Prof. Jacob M. Montgomery Quantitative Political Methodology (L32 363) August 31, 2016 Lecture 2 (QPM 2016) Measurement August 31, 2016 1 / 8 Topics for today A (very) broad view of
More informationTHE GUIDE TO SPSS. David Le
THE GUIDE TO SPSS David Le June 2013 1 Table of Contents Introduction... 3 How to Use this Guide... 3 Frequency Reports... 4 Key Definitions... 4 Example 1: Frequency report using a categorical variable
More informationChapter 1 Data and Descriptive Statistics
1.1 Introduction Chapter 1 Data and Descriptive Statistics Statistics is the art and science of collecting, summarizing, analyzing and interpreting data. The field of statistics can be broadly divided
More informationThe Dummy s Guide to Data Analysis Using SPSS
The Dummy s Guide to Data Analysis Using SPSS Univariate Statistics Scripps College Amy Gamble April, 2001 Amy Gamble 4/30/01 All Rights Rerserved Table of Contents PAGE Creating a Data File...3 1. Creating
More informationValues Auction. Grade Level Take Charge of Your Finances
1.17.4 Values Auction Grade Level 10-12 Take Charge of Your Finances Materials provided by: Linda Majerus, Family and Consumer Sciences Educator, Hobson High School, Hobson, Montana. Deani Goyette Business/Technology
More informationStatistics for Business and Economics
Statistics for Business and Economics Why Study Statistics? Statistics for Business and Economics, 6e 2007 Pearson Education, Inc. Chap 1-1 Dealing with Uncertainty Everyday decisions are based on incomplete
More informationChapter 9 Assignment (due Wednesday, August 9)
Math 146, Summer 2017 Instructor Linda C. Stephenson (due Wednesday, August 9) The purpose of the assignment is to find confidence intervals to predict the proportion of a population. The population in
More informationTime & Expenses: Timesheet
Time & Expenses: Timesheet 1 1. Lab Objectives After completing this lab, you will be able to: Book hours in your timesheet via Outlook retrieval Book hours in your timesheet manually Book expenses via
More informationCompany Activities Part II
QuickBooks Online Student Guide Chapter 12 Company Activities Part II Chapter 2 Chapter 12 In this chapter, you ll learn how QuickBooks handles advanced transactions and tasks in QuickBooks. Growing businesses
More informationSPSS 14: quick guide
SPSS 14: quick guide Edition 2, November 2007 If you would like this document in an alternative format please ask staff for help. On request we can provide documents with a different size and style of
More informationInequality: A Sociological Analysis
Inequality: A Sociological Analysis Assignment Overview: All UNT students who take sociology 1510: Introduction to Sociology (regardless of whom is teaching it) are required to write a research paper.
More informationTutorial Segmentation and Classification
MARKETING ENGINEERING FOR EXCEL TUTORIAL VERSION v171025 Tutorial Segmentation and Classification Marketing Engineering for Excel is a Microsoft Excel add-in. The software runs from within Microsoft Excel
More informationBasic Statistics, Sampling Error, and Confidence Intervals
02-Warner-45165.qxd 8/13/2007 5:00 PM Page 41 CHAPTER 2 Introduction to SPSS Basic Statistics, Sampling Error, and Confidence Intervals 2.1 Introduction We will begin by examining the distribution of scores
More informationHow to Write an Effective Résumé
The Writing Center at OSU Lima Presents How to Write an Effective Résumé (and live to tell about it!) What is a résumé? A résumé is a brief document that summarizes your employment history, education,
More informationCompany Activities Part II
QuickBooks Online Student Guide Chapter 12 Company Activities Part II Chapter 2 Chapter 12 In this chapter, you ll learn how QuickBooks handles advanced transactions and tasks in QuickBooks. Growing businesses
More informationANALYSING QUANTITATIVE DATA
9 ANALYSING QUANTITATIVE DATA Although, of course, there are other software packages that can be used for quantitative data analysis, including Microsoft Excel, SPSS is perhaps the one most commonly subscribed
More informationECON 214 Elements of Statistics for Economists
ECON 214 Elements of Statistics for Economists Session 1 Introduction to Statistics Lecturer: Dr. Bernardin Senadza, Dept. of Economics Contact Information: bsenadza@ug.edu.gh College of Education School
More informationManager Recommendation for Staff Merit Increase
A merit recommender needs to complete a Compensation Planning Worksheet when there is a need for an eligible employee to receive a merit increase. For the 2017 Staff planning year recommenders are only
More informationSPSS Guide Page 1 of 13
SPSS Guide Page 1 of 13 A Guide to SPSS for Public Affairs Students This is intended as a handy how-to guide for most of what you might want to do in SPSS. First, here is what a typical data set might
More information1. A/an is a mathematical statement that calculates a value. 2. Create a cell reference in a formula by typing in the cell name or
Question 1 of 20 : Select the best answer for the question. 1. A/an is a mathematical statement that calculates a value. A. argument B. function C. order of operations D. formula Question 2 of 20 : Select
More informationModule - 01 Lecture - 03 Descriptive Statistics: Graphical Approaches
Introduction of Data Analytics Prof. Nandan Sudarsanam and Prof. B. Ravindran Department of Management Studies and Department of Computer Science and Engineering Indian Institution of Technology, Madras
More information8 Pro Marketing Charts your CEO wants to see
8 Pro Marketing Charts your CEO wants to see and how you can create them in Excel Tell your company s marketing story through stunning charts Marketing has evolved from being an art to being a scientifically
More informationConstant of Proportionality
Constant of Proportionality LAUNCH (6 MIN) Before How can you use the titles on the axes to help you understand the meaning of the graph? Does this graph show a proportional relationship? How can you tell?
More informationECMS Reservations and Payment
ECMS Reservations and Payment User Guide Last Revised: 08-21-18 ECMS Reservations and Payment - User Guide Table of Contents 1. Creating a Reservation for an Event... 3 2. Checking a Reservation using
More informationUsing SPSS for Linear Regression
Using SPSS for Linear Regression This tutorial will show you how to use SPSS version 12.0 to perform linear regression. You will use SPSS to determine the linear regression equation. This tutorial assumes
More informationGush vs. Bore: A Look at the Statistics of Sampling
Gush vs. Bore: A Look at the Statistics of Sampling Open the Fathom file Random_Samples.ftm. Imagine that in a nation somewhere nearby, a presidential election will soon be held with two candidates named
More informationCAREER SERVICES RESOURCE CENTER: CRAFTING YOUR RESUME. CAREER SERVICES AT TEXAS A&M AT GALVESTON (409)
UPDATED 12/8/2016 CAREER SERVICES RESOURCE CENTER: CRAFTING YOUR RESUME CAREER SERVICES AT TEXAS A&M AT GALVESTON www.tamug.edu/career/ (409) 740-4586 THE IMPORTANCE OF A RESUME A resume is an advertisement
More informationLECTURE 17: MULTIVARIABLE REGRESSIONS I
David Youngberg BSAD 210 Montgomery College LECTURE 17: MULTIVARIABLE REGRESSIONS I I. What Determines a House s Price? a. Open Data Set 6 to help us answer this question. You ll see pricing data for homes
More informationApplications & Resumes
Applications & Resumes Completing Your Employment Application and Resume Completing Your Employment Application Complete all requested information. Don t leave anything blank. If you don t know the details,
More informationChapter 19. Confidence Intervals for Proportions. Copyright 2012, 2008, 2005 Pearson Education, Inc.
Chapter 19 Confidence Intervals for Proportions Copyright 2012, 2008, 2005 Pearson Education, Inc. Standard Error Both of the sampling distributions we ve looked at are Normal. For proportions For means
More informationAug 1 9:38 AM. 1. Be able to determine the appropriate display for categorical variables.
Chapter 3 Displaying and Describing Categorical Data Objectives: Students will: 1. Be able to determine the appropriate display for categorical variables. 2. Be able to summarize the distribution of a
More informationCreating a winning CV
Creating a winning CV Introduction The main way to sell yourself on paper is a CV. There is no such thing as one perfect CV; you will produce a number of different CVs to fit different purposes. The chances
More informationVisualizing 2016 presidential election data Apply predominant mapping, Z-Score
Visualizing 2016 presidential election data Apply predominant mapping, Z-Score The 2016 presidential election in the US ended in a surprise victory for Republican candidate Donald Trump. GIS can offer
More informationMGMT 725 Strategic HR Metrics
MGMT 725 Strategic HR Metrics Instructor: E mail: Office: Office Hours: Paul D. Bliese, Ph.D. paul.bliese@moore.sc.edu 410B Mondays and Wednesday, 9:30 11:30am and by appointment. Note that setting up
More informationManager Recommendation for Staff Merit Increase
A merit recommender needs to complete a Compensation Planning Worksheet when there is a need for an eligible employee to receive a merit increase. For the 2018 Staff planning year, recommenders are only
More informationMicrosoft Dynamics GP. Personal Data Keeper
Microsoft Dynamics GP Personal Data Keeper Copyright Copyright 2010 Microsoft. All rights reserved. Limitation of liability This document is provided as-is. Information and views expressed in this document,
More informationADVANCED COMPUTER TECHNOLOGY Excel 2013 Unit Practice Production Test
ADVANCED COMPUTER TECHNOLOGY Excel 2013 Unit Practice Production Test You will create a spreadsheet and two charts that summarize a stock club s current stock holdings. You will also use absolute cell
More informationebusinessoft for Travel Agent Standard Edition AP Guide Copyright Businessoft Sdn Bhd. All rights reserved.
ebusinessoft for Travel Agent Standard Edition AP Guide Copyright 1999-2005 Businessoft Sdn Bhd. All rights reserved. Table of Contents Account Payable (AP)...4 Overview... 4 Vendor...5 Creating Vendor...
More informationThe Master Task Success System. Developed by Mike Scott and Associates
The Master Task Success System Developed by Mike Scott and Associates Copyright 2012 Mike Scott and Associates. All rights reserved. Unauthorized reproduction, in any manner, is prohibited. Using Microsoft
More informationFRACKING AND CLEAN WATER: A SURVEY OF PENNSYLVANIA RESIDENTS. A Survey Conducted for the Civil Society Institute
FRACKING AND CLEAN WATER: A SURVEY OF PENNSYLVANIA RESIDENTS A Survey Conducted for the Civil Society Institute December 21, 2010 Methodology The survey was conducted November 26-30, 2010 among a sample
More information2013A IS4800/CS6350 Midterm Exam Closed Book, Closed Notes, 100 mins max. Name
2013A IS4800/CS6350 Midterm Exam Closed Book, Closed Notes, 100 mins max Name When asked to specify a Study Design please refer to the following list: Ethnographic, Descriptive, Correlational, Demonstrative,
More informationCEE3710: Uncertainty Analysis in Engineering
CEE3710: Uncertainty Analysis in Engineering Lecture 1 September 6, 2017 Why do we need Probability and Statistics?? What is Uncertainty Analysis?? Ex. Consider the average (mean) height of females by
More informationBUSINESS PROGRAMS UNDERGRADUATE PURPOSE 8 HANDBOOK. Business Plan. School of Management, Business Programs
BUSINESS PROGRAMS UNDERGRADUATE PURPOSE 8 HANDBOOK Business Plan School of Management, Business Programs Updated: April 2012 Contents OVERVIEW OF THE PURPOSE Purpose Deliverables, Competencies and their
More informationStreamlining Practice Group Reports BI5
Streamlining Practice Group Reports BI5 Rudolph Vincent Consultant 2012 Redwood Analytics User Conference Analysis. Insight. Action. Objectives: Demonstrate graphing and advanced graphing functionality
More informationStatistical Research Consultants BD (SRCBD) Missing Value Management. Entering missing data in SPSS: web:
Missing Value Management Entering missing data in SPSS: It s likely that your data set will contain some missing values, where participants didn t answer some items on a questionnaire or didn t complete
More informationReal-Time Air Quality Activity. Student Sheets
Real-Time Air Quality Activity Student Sheets Green Group: Location (minimum 3 students) Group Sign-up Sheet Real-time Air Quality Activity 1. 3. 2. Red Group: Time (minimum 4 students) 1. 3. 2. 4. Yellow
More informationMultiple Regression. Dr. Tom Pierce Department of Psychology Radford University
Multiple Regression Dr. Tom Pierce Department of Psychology Radford University In the previous chapter we talked about regression as a technique for using a person s score on one variable to make a best
More informationExcel #2: No magic numbers
Excel #2: No magic numbers This lesson comes from programmers who long ago learned that everything entered into code must be defined and documented. Placing numbers into an equation is dangerous because
More informationEmpirics of Airline Pricing
Empirics of Airline Pricing [Think about a interesting title that will motivate people to read your paper] [you can use this file as a template for your paper. The letters in green are comments and the
More informationExcel 2016: Charts - Full Page
Excel 2016: Charts - Full Page gcflearnfree.org/excel2016/charts/1/ Introduction It can be difficult to interpret Excel workbooks that contain a lot of data. Charts allow you to illustrate your workbook
More informationIntro to PASW (SPSS) Winter Winter 2011 CS130 - Intro to PASW (SPSS) 1
Intro to PASW (SPSS) Winter 2011 Winter 2011 CS130 - Intro to PASW (SPSS) 1 Intro to PASW PASW is a statistical analysis program that allows: Data management in a spreadsheet-like format The ability to
More informationChoosing the best statistical tests for your data and hypotheses. Dr. Christine Pereira Academic Skills Team (ASK)
Choosing the best statistical tests for your data and hypotheses Dr. Christine Pereira Academic Skills Team (ASK) ask@brunel.ac.uk Which test should I use? T-tests Correlations Regression Dr. Christine
More informationNatural Resources Activity: Water Quantity Comparison Design: Just how much do we use?
Name: Lab Partner(s): Date: Class Natural Resources Activity: Water Quantity Comparison Design: Just how much do we use? PART 1: Human uses for water. Using the space below, create a thinking map that
More informationLodging Career Investigation
Ohio FCCLA Lodging Skill Event Lodging Career Investigation DESCRIPTION OF EVENT: Teams comprised of 1-3 participants will develop a career investigation project in the Lodging and Travel Services pathway.
More informationBUSINESS PROGRAMS UNDERGRADUATE PURPOSE 7 HANDBOOK. Managing Capital Markets. School of Management, Business Programs
BUSINESS PROGRAMS UNDERGRADUATE PURPOSE 7 HANDBOOK Managing Capital Markets School of Management, Business Programs Updated: June 2011 Contents OVERVIEW OF THE PURPOSE Purpose Deliverables, Competencies
More informationTwo Way ANOVA. Turkheimer PSYC 771. Page 1 Two-Way ANOVA
Page 1 Two Way ANOVA Two way ANOVA is conceptually like multiple regression, in that we are trying to simulateously assess the effects of more than one X variable on Y. But just as in One Way ANOVA, the
More informationChap1: What Is Statistics?
Chap1: What Is Statistics? Jie Zhang, Ph.D. Student Account and Information Systems Department College of Business Administration The University of Texas at El Paso jzhang6@utep.edu Spring, 2014 Jie Zhang,
More informationPresented by Cristina C. López Associate Director of Career Services St. Thomas University. Rev. 03/15 CL
Presented by Cristina C. López Associate Director of Career Services St. Thomas University 1 Rev. 03/15 CL The résumé is a one-page document that summarizes your skills, work experience, and accomplishments.
More informationEvaluation copy. Biodiversity and Ecosystems. computer OBJECTIVES MATERIALS PROCEDURE
Biodiversity and Ecosystems Computer 29 Biodiversity is critical in any self-sustaining environment. Complex and diverse ecological systems are made up of many organisms and a huge variety of interactions.
More informationTHE NORMAL CURVE AND SAMPLES:
-69- &KDSWHU THE NORMAL CURVE AND SAMPLES: SAMPLING DISTRIBUTIONS A picture of an ideal normal distribution is shown below. The horizontal axis is calibrated in z-scores in terms of standard deviation
More informationUser Manual NSD ERP SYSTEM Customers Relationship Management (CRM)
User Manual Customers Relationship Management (CRM) www.nsdarabia.com Copyright 2009, NSD all rights reserved Table of Contents Introduction... 5 MANAGER S DESKTOP... 5 CUSTOMER RELATIONSHIP MANAGEMENT...
More informationSession 7. Introduction to important statistical techniques for competitiveness analysis example and interpretations
ARTNeT Greater Mekong Sub-region (GMS) initiative Session 7 Introduction to important statistical techniques for competitiveness analysis example and interpretations ARTNeT Consultant Witada Anukoonwattaka,
More informationLecture-16. Data Tables, Scenarios & Goal Seek in Excel 2007
Lecture-16 Data Tables, Scenarios & Goal Seek in Excel 2007 In Excel, a Data Table is a way to see different results by altering an input cell in your formula. As an example, we're going to alert the interest
More informationBlackboard 9 - Calculated Columns
University of Southern California Marshall Information Services Blackboard 9 - Calculated Columns The Blackboard Grade Center allows you to create columns that will display a total based on the numeric
More informationPerformance Management System. Performance Evaluation - Supervisor Step-by-Step Instructions
Performance Management System Performance Evaluation - Supervisor Step-by-Step Instructions Performance Evaluation - Supervisor Step-by-Step Instructions Page 1 of 23 Table of Contents Accessing Performance
More informationDescriptive Statistics Tutorial
Descriptive Statistics Tutorial Measures of central tendency Mean, Median, and Mode Statistics is an important aspect of most fields of science and toxicology is certainly no exception. The rationale behind
More informationUsing the Association Workflow in Partek Genomics Suite
Using the Association Workflow in Partek Genomics Suite This user guide will illustrate the use of the Association workflow in Partek Genomics Suite (PGS) and discuss the basic functions available within
More informationDDBA8437: Central Tendency and Variability Video Podcast Transcript
DDBA8437: Central Tendency and Variability Video Podcast Transcript JENNIFER ANN MORROW: Today's demonstration will review measures of central tendency and variability. My name is Dr. Jennifer Ann Morrow.
More informationRoadway ExpressWORKS to WorldShip Commodity Transfer
Roadway ExpressWORKS to WorldShip Commodity Transfer WorldShip 2000-2014 United Parcel Service of America, Inc. UPS, the UPS brandmark and the color brown are trademarks of United Parcel Service of America,
More informationThe Kruskal-Wallis Test with Excel In 3 Simple Steps. Kilem L. Gwet, Ph.D.
The Kruskal-Wallis Test with Excel 2007 In 3 Simple Steps Kilem L. Gwet, Ph.D. Copyright c 2011 by Kilem Li Gwet, Ph.D. All rights reserved. Published by Advanced Analytics, LLC A single copy of this document
More informationThis week's experiment focuses on bacterial growth and methods to control bacterial growth.
Weekly ilab ilab: Bacterial Growth and Controlling Bacterial Growth Scenario/Summary: This week's experiment focuses on bacterial growth and methods to control bacterial growth. This week's experiment
More informationPerformance Management System
Performance Management System Performance Evaluation - Supervisor Job Aid Performance Evaluation - Supervisor Job Aid Page 1 of 16 When a supervisor s direct report has completed their selfevaluation,
More informationLEARNING RESOURCE CENTRE AYRSHIRE COLLEGE MICROSOFT WORD USEFUL ESSAY FEATURES
LEARNING RESOURCE CENTRE AYRSHIRE COLLEGE MICROSOFT WORD USEFUL ESSAY FEATURES LEARNING RESOURCE CENTRE July 2015 Table of Contents -----------------------------------------------------------------------------------------------------------------------------------
More informationCustomizing the Gantt chart View
In this lab, you will learn how to: Customize a Gantt chart view. LAB # 9 Formatting and Sharing Your Plan Customizing the Gantt chart View The Gantt chart became a standard way of visualizing project
More informationGraded Project Marketing
Graded Project OVERVIEW 1 PROCESS 1 GRADING CRITERIA 5 SUBMITTING YOUR PROJECT 7 C o n t e n t s iii OVERVIEW Objective Design and develop a marketing plan for an existing business. Purpose The purpose
More informationResumes. Types of Resumes
Resumes In essence, a resume is marketing tool that is designed to help you get one step closer to your ultimate goal. A resume needs to be personalized meaning no two resumes should be exactly alike.
More informationDesigning. Presentations. note the color choice: ignoring all these post-its, note the use of simplicity. notice how cluttered this slide is getting.
how long do you think it takes me to make one slide? note the color choice: Designing do I have your this is our last full lecture for this class :( notice how cluttered this slide is getting. attention?
More informationPurchasing Prerequisites and Purchases
Purchasing Purchasing Prerequisites and Purchases Table of Contents Purchase Flow... 3 Purchasing... 4 Purchasing Prerequisites... 5 Expense Accounts... 5 Business Preferences... 7 Business Departments...
More informationLEARN HOW TO CREATE A GREAT RESUME. Presented by: Teresa Flores Roberts Assistant Director, Career Services
LEARN HOW TO CREATE A GREAT RESUME Presented by: Teresa Flores Roberts Assistant Director, Career Services AGENDA What is a Resume? Steps for Writing your Resume Resume Categories Optional Resume Categories
More informationFaculty Guide for Textbook Adoptions. Click here to access the current process for textbook adoptions at CNM.
Faculty Guide for Textbook Adoptions Click here to access the current process for textbook adoptions at CNM. This guide is an addition to the existing process approved for use by Academic Affairs, and
More informationKING ABDULAZIZ UNIVERSITY FACULTY OF COMPUTING & INFORMATION TECHNOLOGY DEPARTMENT OF INFORMATION SYSTEM. Lab 1- Introduction
Lab 1- Introduction Objective: We will start with some basic concept of DSS. And also we will start today the WHAT-IF analysis technique for decision making. Activity Outcomes: What is what-if analysis
More informationCategorical Predictors, Building Regression Models
Fall Semester, 2001 Statistics 621 Lecture 9 Robert Stine 1 Categorical Predictors, Building Regression Models Preliminaries Supplemental notes on main Stat 621 web page Steps in building a regression
More informationLesson 5 Using Lists
QUICKBOOKS 2010: THE BASICS Lesson 5 Using Lists In this lesson, you will learn how to: Work with Customer: Job list Add a new Customer Provide additional Customer information Provide Customer payment
More informationTable of content. B1 Time Task Manual
Table of content Table of content... 1 Overview... 2 Configuration... 2 Prerequisites... 2 Configuration Task... 3 Configuration Time Registration... 4 Configuration Billing... 5 Configuration Permissions...
More informationPrice Setup Wizard: How to Make Global Updates to the Pricebook
Price Setup Wizard: How to Make Global Updates to the Pricebook ServiceTitan Best Practices When it s time to update prices in your Pricebook, ServiceTitan can automate the process for you. Using the Price
More informationPayfirma Brand Guidelines. Communicating the Payfirma Brand
Payfirma Brand Guidelines Communicating the Payfirma Brand 2013 Welcome! 1 This is a guide to the basic elements that make up the Payfirma brand. Have a read, it will help you get to know us a little better.
More informationUse the interactive below to view examples of some of the types of charts that are available in Excel.
Excel 2010 Working with Charts Introduction Page 1 A chart is a tool you can use in Excel to communicate your data graphically. Charts allow your audience to see the meaning behind the numbers, and they
More informationModule 5 Timesheet. Step by Step Guide PSA Suite Basic for CRM Timesheet calendar view 5.2 Timer 5.3 Timesheet by line
Step by Step Guide PSA Suite Basic for CRM 2013 Module 5 5.1 calendar view 5.2 Timer 5.3 by line PSA Suite Basic CRM 2013: V1.0 1 Module 5. Contents TIMESHEET CALENDAR VIEW... 5 INTRODUCTION... 5 1. Objectives...
More informationHow to Make Money Selling a High Demand Novelty Item
How to Make Money Selling a High Demand Novelty Item Copyright 2013 by James J Jones Duplication prohibited Notice This ebook and supplementary material was created to provide specific information regarding
More informationVirtual Lab: What is the relationship between plants and snails?
Virtual Lab: What is the relationship between plants and snails? Directions: Go to our class website. Under Unit 3 materials, click on the link for Plants and Snails Virtual Lab. Use the following information
More informationResume and Cover Letters
Resume and Cover Letters Leslie Coward Program Manager Engineering Career Center What is a Resume? Marketing tool 10-30 second presentation of your experience and knowledge Reflection of the individual
More informationRESUME WRITING A resume Place your job target or objective clearly at the top
Career Services Center 1700 W. Hillsdale Blvd., Building 1, Room 213, San Mateo, CA 94402 P: (650) 574-6116, F: (650) 378-7222, www.collegeofsanmateo.edu/career CSM JobLinks - free online job/internship
More informationCopyright All Rights Reserved
Simple Business Accounting User s guide Version 4 by OWL Software Otto-Williams Ltd. Copyright 1995-2012 All Rights Reserved CONTENTS GETTING STARTED... 1 INTRODUCTION... 1 TECHNICAL SUPPORT... 1 LEARNING
More informationExploring Microsoft Office Excel 2007
Exploring Microsoft Office Excel 2007 Chapter 3: Charts: Delivering a Message Robert Grauer, Keith Mulbery, Judy Scheeren Committed to Shaping the Next Generation of IT Experts. Copyright 2008 Prentice-Hall.
More informationPrinter s Plan Service Release October 27, 2010
1 Printer s Plan 2010 Service Release 2010.07 October 27, 2010 About this release (SR7): Printer s Plan 2010.07 includes all the changes made in the previous Service Releases. If you have not installed
More informationHow to Set-Up a Basic Twitter Page
How to Set-Up a Basic Twitter Page 1. Go to http://twitter.com and find the sign up box, or go directly to https://twitter.com/signup 1 2. Enter your full name, email address, and a password 3. Click Sign
More informationSTAB22 section 2.1. Figure 1: Scatterplot of price vs. size for Mocha Frappuccino
STAB22 section 2.1 2.2 We re changing dog breed (categorical) to breed size (quantitative). This would enable us to see how life span depends on breed size (if it does), which we could assess by drawing
More informationStatistics: Data Analysis and Presentation. Fr Clinic II
Statistics: Data Analysis and Presentation Fr Clinic II Overview Tables and Graphs Populations and Samples Mean, Median, and Standard Deviation Standard Error & 95% Confidence Interval (CI) Error Bars
More information