Part III: Designing Psychological Research In Part II of the course, we discussed what it means to measure psychological variables, and how to do so.

Slides:



Advertisements
Similar presentations
Psychology: A Modular Approach to Mind and Behavior, Tenth Edition, Dennis Coon Appendix Appendix: Behavioral Statistics.
Advertisements

Table of Contents Exit Appendix Behavioral Statistics.
Appendix A. Descriptive Statistics Statistics used to organize and summarize data in a meaningful way.
Introductory Statistics Options, Spring 2008 Stat 100: MWF, 11:00 Science Center C. Stat 100: MWF, 11:00 Science Center C. –General intro to statistical.
Descriptive (Univariate) Statistics Percentages (frequencies) Ratios and Rates Measures of Central Tendency Measures of Variability Descriptive statistics.
Calculating & Reporting Healthcare Statistics
Lesson Fourteen Interpreting Scores. Contents Five Questions about Test Scores 1. The general pattern of the set of scores  How do scores run or what.
Statistical Analysis SC504/HS927 Spring Term 2008 Week 17 (25th January 2008): Analysing data.
Importing our Web data and Answering Descriptive Questions about Single Variables Psych 437.
Central Tendency & Variability Dec. 7. Central Tendency Summarizing the characteristics of data Provide common reference point for comparing two groups.
Measures of Central Tendency
Today: Central Tendency & Dispersion
Describing distributions with numbers
Think of a topic to study Review the previous literature and research Develop research questions and hypotheses Specify how to measure the variables in.
Objective To understand measures of central tendency and use them to analyze data.
Descriptive Statistics Used to describe the basic features of the data in any quantitative study. Both graphical displays and descriptive summary statistics.
Part II Sigma Freud & Descriptive Statistics
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
Overview Summarizing Data – Central Tendency - revisited Summarizing Data – Central Tendency - revisited –Mean, Median, Mode Deviation scores Deviation.
Chapter Eleven A Primer for Descriptive Statistics.
Statistics Recording the results from our studies.
Descriptive Statistics Descriptive Statistics describe a set of data.
Chapter 11 Descriptive Statistics Gay, Mills, and Airasian
Descriptive Statistics
Measures of Dispersion
Nature of Science Science Nature of Science Scientific methods Formulation of a hypothesis Formulation of a hypothesis Survey literature/Archives.
Psyc 235: Introduction to Statistics Lecture Format New Content/Conceptual Info Questions & Work through problems.
© 2006 McGraw-Hill Higher Education. All rights reserved. Numbers Numbers mean different things in different situations. Consider three answers that appear.
Descriptive Statistics
Part III: Designing Psychological Research In Part II of the course, we discussed what it means to measure psychological variables, and how to do so. Now.
An Introduction to Statistics. Two Branches of Statistical Methods Descriptive statistics Techniques for describing data in abbreviated, symbolic fashion.
Descriptive Statistics Descriptive Statistics describe a set of data.
Copyright © 2014 by Nelson Education Limited. 3-1 Chapter 3 Measures of Central Tendency and Dispersion.
Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.
Chapter 11 Univariate Data Analysis; Descriptive Statistics These are summary measurements of a single variable. I.Averages or measures of central tendency.
Measures of Central Tendency: The Mean, Median, and Mode
Univariate Descriptive Research Recall that the objective of univariate descriptive research is to describe a single psychological variable.
Central Tendency & Dispersion
Today’s Questions Once we have collected a large number of measurements, how can we summarize or describe those measurements most effectively by using.
Chapter Eight: Using Statistics to Answer Questions.
Unit 2 (F): Statistics in Psychological Research: Measures of Central Tendency Mr. Debes A.P. Psychology.
IE(DS)1 Descriptive Statistics Data - Quantitative observation of Behavior What do numbers mean? If we call one thing 1 and another thing 2 what do we.
Statistical Analysis of Data. What is a Statistic???? Population Sample Parameter: value that describes a population Statistic: a value that describes.
Descriptive Statistics. Outline of Today’s Discussion 1.Central Tendency 2.Dispersion 3.Graphs 4.Excel Practice: Computing the S.D. 5.SPSS: Existing Files.
LIS 570 Summarising and presenting data - Univariate analysis.
Aron, Aron, & Coups, Statistics for the Behavioral and Social Sciences: A Brief Course (3e), © 2005 Prentice Hall Chapter 2 The Mean, Variance, Standard.
Outline of Today’s Discussion 1.Displaying the Order in a Group of Numbers: 2.The Mean, Variance, Standard Deviation, & Z-Scores 3.SPSS: Data Entry, Definition,
Anthony J Greene1 Central Tendency 1.Mean Population Vs. Sample Mean 2.Median 3.Mode 1.Describing a Distribution in Terms of Central Tendency 2.Differences.
Descriptive Statistics Research Writing Aiden Yeh, PhD.
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.
1 Research Methods in Psychology AS Descriptive Statistics.
Descriptive Statistics(Summary and Variability measures)
Copyright © 2016 Brooks/Cole Cengage Learning Intro to Statistics Part II Descriptive Statistics Intro to Statistics Part II Descriptive Statistics Ernesto.
Educational Research Descriptive Statistics Chapter th edition Chapter th edition Gay and Airasian.
CHAPTER 11 Mean and Standard Deviation. BOX AND WHISKER PLOTS  Worksheet on Interpreting and making a box and whisker plot in the calculator.
Chapter 2 The Mean, Variance, Standard Deviation, and Z Scores.
Lecture 8 Data Analysis: Univariate Analysis and Data Description Research Methods and Statistics 1.
Different Types of Data
Intro to Statistics Part II Descriptive Statistics
Univariate Statistics
Numerical Measures: Centrality and Variability
Summary descriptive statistics: means and standard deviations:
STATS DAY First a few review questions.
Chapter 2 The Mean, Variance, Standard Deviation, and Z Scores
Module 8 Statistical Reasoning in Everyday Life
Part III: Designing Psychological Research
Summary descriptive statistics: means and standard deviations:
Statistics: The Interpretation of Data
Basic Biostatistics Measures of central tendency and dispersion
Presentation transcript:

Part III: Designing Psychological Research In Part II of the course, we discussed what it means to measure psychological variables, and how to do so.

Different kinds of research questions In the next few weeks, we’ll begin to talk about some of the ways that research can be designed in order to answer both basic and applied research questions. Some of the key questions we’ll have to ask ourselves throughout this process are: –does this question involve one variable or more than one variable and – does the question concern the causal nature of the relationship between two or more variables?

Different kinds of research questions Descriptive UnivariateMultivariate CausalDescriptive

Different kinds of research questions Univariate: questions pertaining to a single variable –how long are people married, on average, before they have children? –how many adults were sexually abused as children? Descriptive research is used to provide a systematic description of a psychological phenomenon.

Different kinds of research questions Multivariate: questions pertaining to the relationship between two or more variables –How does marital satisfaction vary as a function of the length of time that a couple waits before having children? –Are people who were sexually abused as children more likely to be anxious, depressed, or insecure as adults?

Different kinds of research questions Notice that in each of these cases there is no assumption that one variable necessarily causes the other. In contrast, causal research focuses on how variables influence one another –Does psychotherapy help to improve peoples’ well-being? –Does drinking coffee while studying increase test performance?

Different kinds of research questions Descriptive UnivariateMultivariate CausalDescriptive

Univariate Descriptive Research The objective of univariate descriptive research is to describe a single psychological variable.

Univariate Descriptive Research Before we can describe the variable, we need to know whether it is categorical or continuous. This will impact the way we go about describing the variable. If the variable is categorical, all we need to do to answer the question is see what proportion of people fall into the various categories.

Categorical Variable Example research question: What is the gender of students enrolled as psychology majors at UIC? We can obtain a random sample of psychology majors at UIC. Measure the sex of participants (a simple self-report question should suffice) See what proportion of people are male vs. female.

PersonSex ThomasM EricM ClaudiaF JennyF JenniF CarolineF MarcM ShamaraF LisaF Males: 3 Females: 6 Total: Males: 33% [3/9] Females: 66% [6/9]

Continuous Variable When the variable is continuous it doesn’t make sense to use “proportions” to answer the research question. Example: How stressed is an average psychology student at UIC? To answer this question, we need to describe the distribution of scores.

Example How stressed have you been in the last 2 ½ weeks? Scale: 0 (not at all) to 10 (as stressed as possible) How can we summarize this information effectively?

Frequency Tables A frequency table shows how often each value of the variable occurs Stress rating Frequency

Frequency Polygon A visual representation of information contained in a frequency table Align all possible values on the bottom of the graph (the x-axis) On the vertical line (the y-axis), place a point denoting the frequency of scores for each value Connect the lines (typically add an extra value above and below the actual range of values—in this example, at –1 and 11)

Measures of Central Tendency Central tendency: most “typical” or common score (a) Mode (b) Median (c) Mean

Measures of Central Tendency 1. Mode: most frequently occurring score Mode = 7

Measures of Central Tendency 2. Median: the value at which 1/2 of the ordered scores fall above and 1/2 of the scores fall below Median = 3Median = 2.5

Measures of Central Tendency 2. Median: the value at which 1/2 of the ordered scores fall above and 1/2 of the scores fall below … … Median = 7

Measures of Central Tendency x = an individual score N = the number of scores Sigma or  = take the sum Note: Equivalent to saying “sum all the scores and divide that sum by the total number of scores” 3. Mean: The “balancing point” of a set of scores; the average

Measures of Central Tendency Mean = ( )/10 = 3

Mean In the stress example, the sum of all the scores is / 151 = 6.5 Thus, the average score is 6.5, on a 0 to 10 scale.

Median vs. Mean suppose there are 7 people who graduate from some university with degrees in communications. They all get jobs, and their salaries are: $27,000 $29,000 $33,000 $34,000 $35,000 $39,000 $5,000,000 The last guy got a job playing basketball in the NBA! Now, the median is the middle value, or $34,000. But the mean is about $750,000.

Spread Notice that not everyone has a score of 6.5 Some people have very low scores (e.g., 0), and some people have very high scores (e.g., 10). The degree to which there is variation in the scores (i.e., people’s scores differ) is referred to as the dispersion or spread of the scores.

Measures of Spread To illustrate the way differences in spread may look, consider this graph. Two sets of scores with the same mean, but different spreads.

Standard Deviation The most common way of quantifying dispersion is with an index called the standard deviation. The SD is an average, and can be interpreted as the average amount of dispersion around the mean. Larger SD = more dispersion.

Recipe for Computing the Standard Deviation First, find the mean of the scores. Let’s call this M. Second, subtract each score from the mean. Third, square each of these differences. Fourth, average these squared differences. Fifth, take the square root of this average.

PersonScore or x(x – M)(x – M) 2 Homer1(1 – 4) = = 9 Maggie2(2 – 4) = = 4 Lisa2(2 – 4) = = 4 Bart4(4 – 4) = 00 2 = 0 Marge8(8 – 4) = 44 2 = 16 Santa7(7 – 4) = 33 2 = 9

How to Verbally Summarize this Information In this example, we see that the average stress score is 4, on a scale ranging from 1 to 8. Not everyone has a score of 4, however. On average, people are 2.6 units away from the mean.

Summary Most descriptive questions concerning one variable can be answered pretty easily. If the variable is categorical, –determine the proportion of people in each category or level of the variable If the variable is continuous, –find the mean and standard deviation of the scores.