[title of your research project]

Slides:



Advertisements
Similar presentations
Critical Reading Strategies: Overview of Research Process
Advertisements

Chapter 9: Simple Regression Continued
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.
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.
Chapter 16 Quantitative Proposals and Reports. WRITING QUANTITATIVE RESEARCH PROPOSALS Part 1: Research Topic Part 1: Research Topic Part 2: Literature.
Research Design After: finding an interesting research question; finding an interesting research question; reviewing the literature on the topic area;
Correlational Designs
Simple Linear Regression Analysis
Factor Analysis Psy 524 Ainsworth.
Active Learning Lecture Slides
Chapter 2: The Research Enterprise in Psychology
Research Methods. Research Projects  Background Literature  Aims and Hypothesis  Methods: Study Design Data collection approach Sample Size and Power.
Introduction to Linear Regression and Correlation Analysis
Chapter 13: Inference in Regression
Chapter 11 Simple Regression
Chapter 2: The Research Enterprise in Psychology
STA291 Statistical Methods Lecture 27. Inference for Regression.
Things that I think are important Chapter 1 Bar graphs, histograms Outliers Mean, median, mode, quartiles of data Variance and standard deviation of.
Impact of business environment on poverty reduction Gessye Ginelle Safou-Mat American University School of International Service.
Research Process Research Process Step One – Conceptualize Objectives Step One – Conceptualize Objectives Step Two – Measure Objectives Step Two – Measure.
Statistics for Decision Making Bivariate Descriptive Statistics QM Fall 2003 Instructor: John Seydel, Ph.D.
Statistics Definition Methods of organizing and analyzing quantitative data Types Descriptive statistics –Central tendency, variability, etc. Inferential.
Chapter 1: The Research Enterprise in Psychology.
Econ 3790: Business and Economics Statistics Instructor: Yogesh Uppal
1 1 Slide © 2008 Thomson South-Western. All Rights Reserved Chapter 15 Multiple Regression n Multiple Regression Model n Least Squares Method n Multiple.
L 1 Chapter 12 Correlational Designs EDUC 640 Dr. William M. Bauer.
UNDERSTANDING RESEARCH RESULTS: DESCRIPTION AND CORRELATION © 2012 The McGraw-Hill Companies, Inc.
Chapter 16 The Elaboration Model Key Terms. Descriptive statistics Statistical computations describing either the characteristics of a sample or the relationship.
Statistical Methods Statistical Methods Descriptive Inferential
© 2008 McGraw-Hill Higher Education The Statistical Imagination Chapter 15: Correlation and Regression Part 2: Hypothesis Testing and Aspects of a Relationship.
WHY RPW?. OBJECTIVES OF THE COURSE SOURCES OF RESEARCH QUESTIONS Primary research (printed, electronic) Secondary: Books Position papers Literature Reviews.
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 and Regression Basic Concepts. An Example We can hypothesize that the value of a house increases as its size increases. Said differently,
Chapter 13 Multiple Regression
The Statistical Imagination Chapter 15. Correlation and Regression Part 2: Hypothesis Testing and Aspects of a Relationship.
Statistical planning and Sample size determination.
The Research Process Step 1-4 IBC464 International College
[title of your research project] [author] INST 381 Fall 2015.
SIMAD University Chapter one Introduction Ali Yassin Sheikh.
Lesson 14 - R Chapter 14 Review. Objectives Summarize the chapter Define the vocabulary used Complete all objectives Successfully answer any of the review.
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.
Descriptive Statistics
The Process of Conducting Research. What is a theory? a set of general principles that explains the how and why of phenomena. Theories are not directly.
+ EXPERIMENTAL INVESTIGATIONS An experimental investigation is one in which a control is identified. The variables are measured in an effort to gather.
Correlation and Regression Basic Concepts. An Example We can hypothesize that the value of a house increases as its size increases. Said differently,
Multiple Regression Reference: Chapter 18 of Statistics for Management and Economics, 7 th Edition, Gerald Keller. 1.
Statistics and probability Dr. Khaled Ismael Almghari Phone No:
Intro to Research Methods
Chapter 20 Linear and Multiple Regression
REGRESSION G&W p
STAT 4030 – Programming in R STATISTICS MODULE: Basic Data Analysis
Review 1. Describing variables.
Chapter 5 LSRL.
Correlation and regression
STAT 4030 – Programming in R STATISTICS MODULE: Confidence Intervals
Regression Statistics
BIVARIATE REGRESSION AND CORRELATION
HMI 7530– Programming in R STATISTICS MODULE: Confidence Intervals
HMI 7530– Programming in R STATISTICS MODULE: Basic Data Analysis
AP Research Paper Components
Statistics II: An Overview of Statistics
Reasoning in Psychology Using Statistics
Reasoning in Psychology Using Statistics
Research process.
Table 2. Regression statistics for independent and dependent variables
Introductory Statistics
Presentation transcript:

[title of your research project] [author] INST 381 [semester] [year]

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:

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 Variables min mean median max standard deviation % missing [varname]

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

Regression Model [name of dependent variable] = β0 + β1*[name of 1st independent variable] + β2*[name of 2nd independent variable] + β3*[possible interaction between two independent variables if applicable] + β4*[name of another independent or control variable in the regression model] + [...]

[sample] Regression Results variables 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) (0.072) -2.010* (1.023) -1.910 (1.021) (1.029) 4.887* (2.454) 4.239 (2.544) -0.020 (0.020) -0.019 ... R-square 0.133 0.156 0.177 N 200 *: 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].

Bibliography [four references (academic journal articles, book chapters, etc.]