[title of your research project] [author] INST 381 Fall 2015.

Slides:

Advertisements

Similar presentations

Critical Reading Strategies: Overview of Research Process

Advertisements

Lesson 10: Linear Regression and Correlation

1 1 Chapter 5: Multiple Regression 5.1 Fitting a Multiple Regression Model 5.2 Fitting a Multiple Regression Model with Interactions 5.3 Generating and.

Irwin/McGraw-Hill © Andrew F. Siegel, 1997 and l Chapter 12 l Multiple Regression: Predicting One Factor from Several Others.

Economics 105: Statistics GH 24 due Wednesday. Hypothesis Tests on Several Regression Coefficients Consider the model (expanding on GH 22) Is “race” as.

Correlation & Regression Chapter 15. Correlation statistical technique that is used to measure and describe a relationship between two variables (X and.

Statistics II: An Overview of Statistics. Outline for Statistics II Lecture: SPSS Syntax – Some examples. Normal Distribution Curve. Sampling Distribution.

GRAPHS OF MEANS How is a Graph of Means Constructed? What are Error Bars? How Can a Graph Indicate Statistical Significance?

Chapter 16 Quantitative Proposals and Reports. WRITING QUANTITATIVE RESEARCH PROPOSALS Part 1: Research Topic Part 1: Research Topic Part 2: Literature.

CHAPTER 4 ECONOMETRICS x x x x x Multiple Regression = more than one explanatory variable Independent variables are X 2 and X 3. Y i = B 1 + B 2 X 2i +

The research process Psych 231: Research Methods in Psychology.

STRATEGIES FOR RESEARCH Approaching the Paper Assignment.

The research process Psych 231: Research Methods in Psychology.

Ch. 14: The Multiple Regression Model building

Correlational Designs

Correlation and Regression Analysis

Simple Linear Regression Analysis

Factor Analysis Psy 524 Ainsworth.

Hypothesis Construction Claude Oscar Monet: The Blue House in Zaandam, 1871.

Active Learning Lecture Slides

Chapter 2: The Research Enterprise in Psychology

Introduction to Linear Regression and Correlation Analysis

Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 12 Analyzing the Association Between Quantitative Variables: Regression Analysis Section.

Chapter 13: Inference in Regression

STA291 Statistical Methods Lecture 27. Inference for Regression.

Chapter 1: The Research Enterprise in Psychology.

Econ 3790: Business and Economics Statistics Instructor: Yogesh Uppal

L 1 Chapter 12 Correlational Designs EDUC 640 Dr. William M. Bauer.

● Final exam Wednesday, 6/10, 11:30-2:30. ● Bring your own blue books ● Closed book. Calculators and 2-page cheat sheet allowed. No cell phone/computer.

Chapter 16 The Elaboration Model Key Terms. Descriptive statistics Statistical computations describing either the characteristics of a sample or the relationship.

Applied Quantitative Analysis and Practices LECTURE#23 By Dr. Osman Sadiq Paracha.

Statistical Methods Statistical Methods Descriptive Inferential

Lab 5 instruction.  a collection of statistical methods to compare several groups according to their means on a quantitative response variable  Two-Way.

© 2008 McGraw-Hill Higher Education The Statistical Imagination Chapter 15: Correlation and Regression Part 2: Hypothesis Testing and Aspects of a Relationship.

Ordinary Least Squares Estimation: A Primer Projectseminar Migration and the Labour Market, Meeting May 24, 2012 The linear regression model 1. A brief.

PY 603 – Advanced Statistics II TR 12:30-1:45pm 232 Gordon Palmer Hall Jamie DeCoster.

Review of Research Methods. Overview of the Research Process I. Develop a research question II. Develop a hypothesis III. Choose a research design IV.

CORRELATION: Correlation analysis Correlation analysis is used to measure the strength of association (linear relationship) between two quantitative variables.

Correlation and Regression Basic Concepts. An Example We can hypothesize that the value of a house increases as its size increases. Said differently,

Discussion of time series and panel models

Welcome to Econ 420 Applied Regression Analysis Study Guide Week Four Ending Wednesday, September 19 (Assignment 4 which is included in this study guide.

Research Project Title Researcher Name #1 Researcher Name #2 Researcher Name #3 Researcher Name #4 Date of Presentation Name of Conference Presenting at.

The Statistical Imagination Chapter 15. Correlation and Regression Part 2: Hypothesis Testing and Aspects of a Relationship.

Statistical planning and Sample size determination.

Click to edit Master title style Midterm 3 Wednesday, June 10, 1:10pm.

The Research Process Step 1-4 IBC464 International College

Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Simple Linear Regression Analysis Chapter 13.

1 UNIT 13: DATA ANALYSIS. 2 A. Editing, Coding and Computer Entry Editing in field i.e after completion of each interview/questionnaire. Editing again.

Chapter 16 Multiple Regression and Correlation

Research Methodology Lecture No :26 (Hypothesis Testing – Relationship)

+ EXPERIMENTAL INVESTIGATIONS An experimental investigation is one in which a control is identified. The variables are measured in an effort to gather.

Lec. 19 – Hypothesis Testing: The Null and Types of Error.

Economics 173 Business Statistics Lecture 18 Fall, 2001 Professor J. Petry

Correlation and Regression Basic Concepts. An Example We can hypothesize that the value of a house increases as its size increases. Said differently,

Chapter 20 Linear and Multiple Regression

REGRESSION G&W p

STAT 4030 – Programming in R STATISTICS MODULE: Basic Data Analysis

Review 1. Describing variables.

26134 Business Statistics Week 5 Tutorial

BIVARIATE REGRESSION AND CORRELATION

الإحصاء ومنهجية البحث Statistics and Research Methodology Fall 2016

Title Goes Here Title Goes Here Title Goes Here Title Goes Here

HMI 7530– Programming in R STATISTICS MODULE: Basic Data Analysis

Student Name: Student Id: Supervisor’s Name:

[title of your research project]

Hypothesis Construction

Simple Linear Regression

AP Research Paper Components

Statistics II: An Overview of Statistics

Scientific Method Notes

Presentation transcript:

[title of your research project] [author] INST 381 Fall 2015

Research Question [Empirical puzzle or theoretical debate] [photo, picture, or infographics optional]

Causal Theory Literature Review [Your contribution]

Hypotheses Hypothesis 1: – [all else being equal,...] Hypothesis 2: – [all else being equal,...]

Dependent Variable Conceptual definition: – [] Operational definition: – []

Independent Variable(s) Conceptual definition: – [] Operational definition: – []

The Data [brief description/citation of the data] [principal investigators] [geographic coverage] [time period/date of collection] [unit of observation, e.g. individuals, states...] [sampling method] [how the data was collected]

Descriptive Statistics Variablesminmeanmedianmaxstandard deviation % missing [varname]

[descriptive charts optional] [bar, line, histogram, and/or scatterplot...]

Regression Model [name of dependent variable] = β 0 + β 1 *[name of 1st independent variable] + β 2 *[name of 2nd independent variable] + β 3 *[possible interaction between two independent variables if applicable] + β 4 *[name of another independent or control variable in the regression model] + [...]

[sample] Regression Results variablesCoefficient estimate Standard error Coefficient estimate Standard error Coefficient estimate Standard error (Constant)12.325***(3.194)11.785***(3.187)11.316***(3.199) [variable]0.389***(0.074)0.354***(0.073)0.389***(0.072) [variable]-2.010*(1.023)-1.910(1.021)-2.010*(1.029) [variable]4.887*(2.454)4.239(2.544) [variable]-0.020(0.020)-0.019(0.020) ***(0.072) *(1.029) (2.544) R-square N200 *: p<0.1; **: p<0.05; ***: p<0.01

Estimated Regression Equation(s) [name of dependent variable] = [value of coefficient estimate] + [value of coefficient estimate]*[name of 1st independent variable] + [value of coefficient estimate]*[name of 2nd independent variable] + [value of coefficient estimate]*[name of another independent or control variable in the regression model] + [...] [if interaction write two separate equations]

Interpret the Regression Results The regression coefficient for [1st independent variable] is [/not] statistically significant at the 5 per cent level. Controlling for the other variables, a one-unit increase in the [1st independent variable] is associated with a [value of the coefficient estimate] [increase/decrease] in the [name of the dependent variable].

Interpret the Regression Results The regression coefficient for [2nd independent variable] is [/not] statistically significant at the 5 per cent level. Controlling for the other variables, a one-unit increase in the [2nd independent variable] is associated with a [value of the coefficient estimate] [increase/decrease] in the [name of the dependent variable].

Interpret the Regression Results [other interesting findings from the regression, such as changes in the value of adjusted R-square, coefficient estimates for interaction terms and/or for other control variables].